Fixed Point Learning Based Intelligent Traffic Control System

NASA Astrophysics Data System (ADS)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

An Intelligent Computer Assisted Language Learning System for Arabic Learners

ERIC Educational Resources Information Center

Shaalan, Khaled F.

2005-01-01

This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning…

Multi-Agent Framework for Virtual Learning Spaces.

ERIC Educational Resources Information Center

Sheremetov, Leonid; Nunez, Gustavo

1999-01-01

Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

Research and Conceptualization of Ontologies in Intelligent Learning Systems

ERIC Educational Resources Information Center

Deliyska, Boryana; Manoilov, Peter

2010-01-01

The intelligent learning systems provide direct customized instruction to the learners without the intervention of human tutors on the basis of Semantic Web resources. Principal roles use ontologies as instruments for modeling learning processes, learners, learning disciplines and resources. This paper examines the variety, relationships, and…

What have we learned about intelligent transportation systems? Chapter 2, What have we learned about freeway incident and emergency management and electronic toll collection?

DOT National Transportation Integrated Search

2000-12-01

The intelligent infrastructure is often the most visible manifestation of intelligent transportation systems (ITS) along with roads, freeways, and incident management is often among the first ITS elements implemented. They can significantly contribut...

Developing Self-Regulated Learners through an Intelligent Tutoring System

ERIC Educational Resources Information Center

Kelly, Kim; Heffernan, Neil

2015-01-01

Intelligent tutoring systems have been developed to help students learn independently. However, students who are poor self-regulated learners often struggle to use these systems because they lack the skills necessary to learn independently. The field of psychology has extensively studied self-regulated learning and can provide strategies to…

Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.

PubMed

Xu, Bin; Sun, Fuchun

2018-02-01

This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.

An Intelligent Learning Diagnosis System for Web-Based Thematic Learning Platform

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Liu, Ming-Chou; Chu, San-Shine; Cheng, Chih-Lun

2007-01-01

This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners' ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to…

Perceptions of the use of intelligent information access systems in university level active learning activities among teachers of biomedical subjects.

PubMed

Aparicio, Fernando; Morales-Botello, María Luz; Rubio, Margarita; Hernando, Asunción; Muñoz, Rafael; López-Fernández, Hugo; Glez-Peña, Daniel; Fdez-Riverola, Florentino; de la Villa, Manuel; Maña, Manuel; Gachet, Diego; Buenaga, Manuel de

2018-04-01

Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education. The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers. Eleven teachers of degree courses who belonged to the Faculties of Biomedical Sciences (BS) and Health Sciences (HS) of a Spanish university in Madrid were individually interviewed. These interviews were conducted using a mixed methods questionnaire that included 66 predefined close-ended and open-ended questions. In our study, three intelligent information access systems (i.e., BioAnnote, CLEiM and MedCMap) were successfully used to evaluate the teacher's perceptions regarding the utility of these systems and their different methods in learning activities. All teachers reported using active learning methods in the classroom, most of which were computer programs that were used for initially designing and later executing learning activities. All teachers used case-based learning methods in the classroom, with a specific emphasis on case reports written in Spanish and/or English. In general, few or none of the teachers were familiar with the technical terms related to the technologies used for these activities such as "intelligent systems" or "concept/mental maps". However, they clearly realized the potential applicability of such approaches in both the preparation and the effective use of these activities in the classroom. Specifically, the themes highlighted by a greater number of teachers after analyzing the responses to the open-ended questions were the usefulness of BioAnnote system to provide reliable sources of medical information and the usefulness of the bilingual nature of CLEiM system for learning medical terminology in English. Three intelligent information access systems were successfully used to evaluate the teacher's perceptions regarding the utility of these systems in learning activities. The results of this study showed that integration of reliable sources of information, bilingualism and selective annotation of concepts were the most valued features by the teachers, who also considered the incorporation of these systems into learning activities to be potentially very useful. In addition, in the context of our experimental conditions, our work provides useful insights into the way to appropriately integrate this type of intelligent information access systems into learning activities, revealing key themes to consider when developing such approaches. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Development of cyberblog-based intelligent tutorial system to improve students learning ability algorithm

NASA Astrophysics Data System (ADS)

Wahyudin; Riza, L. S.; Putro, B. L.

2018-05-01

E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.

A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

ERIC Educational Resources Information Center

de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

2017-01-01

Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

PubMed

Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

2016-07-01

We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Analysis of Student Model Portability

ERIC Educational Resources Information Center

Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict

2016-01-01

Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

NASA Technical Reports Server (NTRS)

Chen, Alexander Y.

1990-01-01

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Development and Evaluation of Intelligent Agent-Based Teaching Assistant in e-Learning Portals

ERIC Educational Resources Information Center

Rouhani, Saeed; Mirhosseini, Seyed Vahid

2015-01-01

Today, several educational portals established by organizations to enhance web E-learning. Intelligence agent's usage is necessary to improve the system's quality and cover limitations such as face-to-face relation. In this research, after finding two main approaches in this field that are fundamental use of intelligent agents in systems design…

Clustering and Profiling Students According to Their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Harley, Jason M.; Trevors, Gregory J.; Azevedo, Roger

2013-01-01

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…

Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

ERIC Educational Resources Information Center

Rastegarmoghadam, Mahin; Ziarati, Koorush

2017-01-01

Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

Automatic Presentation of Sense-Specific Lexical Information in an Intelligent Learning System

ERIC Educational Resources Information Center

Eom, Soojeong

2012-01-01

Learning vocabulary and understanding texts present difficulty for language learners due to, among other things, the high degree of lexical ambiguity. By developing an intelligent tutoring system, this dissertation examines whether automatically providing enriched sense-specific information is effective for vocabulary learning and reading…

A Multi-Agent System Approach for Distance Learning Architecture

ERIC Educational Resources Information Center

Turgay, Safiye

2005-01-01

The goal of this study is to suggest the agent systems by intelligence and adaptability properties in distance learning environment. The suggested system has flexible, agile, intelligence and cooperation features. System components are teachers, students (learners), and resources. Inter component relations are modeled and reviewed by using the…

The TENOR Architecture for Advanced Distributed Learning and Intelligent Training

DTIC Science & Technology

2002-01-01

called TENOR, for Training Education Network on Request. There have been a number of recent learning systems developed that leverage off Internet...AG2-14256 AIAA 2002-1054 The TENOR Architecture for Advanced Distributed Learning and Intelligent Training C. Tibaudo, J. Kristl and J. Schroeder...COVERED 4. TITLE AND SUBTITLE The TENOR Architecture for Advanced Distributed Learning and Intelligent Training 5a. CONTRACT NUMBER F33615-00-M

Effective e-learning for health professional and medical students: the experience with SIAS-Intelligent Tutoring System.

PubMed

Muñoz, Diana C; Ortiz, Alexandra; González, Carolina; López, Diego M; Blobel, Bernd

2010-01-01

Current e-learning systems are still inadequate to support the level of interaction, personalization and engagement demanded by clinicians, care givers, and the patient themselves. For effective e-learning to be delivered in the health context, collaboration between pedagogy and technology is required. Furthermore, e-learning systems should be flexible enough to be adapted to the students' needs, evaluated regularly, easy to use and maintain and provide students' feedback, guidelines and supporting material in different formats. This paper presents the implementation of an Intelligent Tutoring System (SIAS-ITS), and its evaluation compared to a traditional virtual learning platform (Moodle). The evaluation was carried out as a case study, in which the participants were separated in two groups, each group attending a virtual course on the WHO Integrated Management of Childhood Illness (IMCI) strategy supported by one of the two e-learning platforms. The evaluation demonstrated that the participants' knowledge level, pedagogical strategies used, learning efficiency and systems' usability were improved using the Intelligent Tutoring System.

Some Steps towards Intelligent Computer Tutoring Systems.

ERIC Educational Resources Information Center

Tchogovadze, Gotcha G.

1986-01-01

Describes one way of structuring an intelligent tutoring system (ITS) in light of developments in artificial intelligence. A specialized intelligent operating system (SIOS) is proposed for software for a network of microcomputers, and it is postulated that a general learning system must be used as a basic framework for the SIOS. (Author/LRW)

The Impact of Integrated Coaching and Collaboration within an Inquiry Learning Environment

ERIC Educational Resources Information Center

Dragon, Toby

2013-01-01

This thesis explores the design and evaluation of a collaborative, inquiry learning Intelligent Tutoring System for ill-defined problem spaces. The common ground in the fields of Artificial Intelligence in Education and Computer-Supported Collaborative Learning is investigated to identify ways in which tutoring systems can employ both automated…

A Conversational Intelligent Tutoring System to Automatically Predict Learning Styles

ERIC Educational Resources Information Center

Latham, Annabel; Crockett, Keeley; McLean, David; Edmonds, Bruce

2012-01-01

This paper proposes a generic methodology and architecture for developing a novel conversational intelligent tutoring system (CITS) called Oscar that leads a tutoring conversation and dynamically predicts and adapts to a student's learning style. Oscar aims to mimic a human tutor by implicitly modelling the learning style during tutoring, and…

Integration of an Intelligent Tutoring System in a Course of Computer Network Design

ERIC Educational Resources Information Center

Verdú, Elena; Regueras, Luisa M.; Gal, Eran; de Castro, Juan P.; Verdú, María J.; Kohen-Vacs, Dan

2017-01-01

INTUITEL is a research project aiming to offer a personalized learning environment. The INTUITEL approach includes an Intelligent Tutoring System that gives students recommendations and feedback about what the best learning path is for them according to their profile, learning progress, context and environmental influences. INTUITEL combines…

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

"Lessons learned" : evaluation of intelligent transportation systems (ITS) implementation at Santee Wateree Regional Transportation Authority.

DOT National Transportation Integrated Search

2002-06-01

The purpose of this lessons learned is to document the experience with Intelligent Transportation Systems (ITS) : implementation at the Santee Wateree Regional Transportation authority (SWRTA). SWRTA is a public : transportation provider servin...

E-learning environment as intelligent tutoring system

NASA Astrophysics Data System (ADS)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Systems autonomy

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.

1988-01-01

Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.

Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field

ERIC Educational Resources Information Center

Magnisalis, I.; Demetriadis, S.; Karakostas, A.

2011-01-01

This study critically reviews the recently published scientific literature on the design and impact of adaptive and intelligent systems for collaborative learning support (AICLS) systems. The focus is threefold: 1) analyze critical design issues of AICLS systems and organize them under a unifying classification scheme, 2) present research evidence…

A Solution-Based Intelligent Tutoring System Integrated with an Online Game-Based Formative Assessment: Development and Evaluation

ERIC Educational Resources Information Center

Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Abdollahi, Abbas; Horng, Shi-Jinn; Lim, Heuiseok

2016-01-01

Nowadays, intelligent tutoring systems are considered an effective research tool for learning systems and problem-solving skill improvement. Nonetheless, such individualized systems may cause students to lose learning motivation when interaction and timely guidance are lacking. In order to address this problem, a solution-based intelligent…

Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

DTIC Science & Technology

2016-06-01

research is being done to incorporate the field of machine learning into intrusion detection. Machine learning is a branch of artificial intelligence (AI...adversarial drift." Proceedings of the 2013 ACM workshop on Artificial intelligence and security. ACM. (2013) Kantarcioglu, M., Xi, B., and Clifton, C. "A...34 Proceedings of the 4th ACM workshop on Security and artificial intelligence . ACM. (2011) Dua, S., and Du, X. Data Mining and Machine Learning in

Suitable Learning Styles for Intelligent Tutoring Technologies (Styles d’Apprentissage Appropries pour les Technologies Tuteurs Intelligents)

DTIC Science & Technology

2010-05-01

mind, (ii) forms of mental self-government, and (iii) stylistic preferences. Importantly, Sternberg does not think that cognitive style...summarizes a study examining suitable cognitive and learning styles for intelligent tutoring technologies to improve the Canadian Forces (CF) distance...are the appropriate tool to address CF learning needs, as e-learning systems: • Cater to all individuals in the CF regardless of their cognitive or

Using a Problem-Based Learning Approach to Teach an Intelligent Systems Course

ERIC Educational Resources Information Center

Cheong, France

2008-01-01

While delivering the Intelligent Systems course, an elective course in the Master of Business Information Technology program at RMIT University, it was felt that there was a learning issue as students' learning seemed to be superficial. This perception was based on the questions students asked in class and the mechanical attitude they adopted…

The Impact of Game-Like Features on Learning from an Intelligent Tutoring System

ERIC Educational Resources Information Center

Millis, Keith; Forsyth, Carol; Wallace, Patricia; Graesser, Arthur C.; Timmins, Gary

2017-01-01

Prior research has shown that students learn from Intelligent Tutoring Systems (ITS). However, students' attention may drift or become disengaged with the task over extended amounts of instruction. To remedy this problem, researchers have examined the impact of game-like features (e.g., a narrative) in digital learning environments on motivation…

Note-Taking within MetaTutor: Interactions between an Intelligent Tutoring System and Prior Knowledge on Note-Taking and Learning

ERIC Educational Resources Information Center

Trevors, Gregory; Duffy, Melissa; Azevedo, Roger

2014-01-01

Hypermedia learning environments (HLE) unevenly present new challenges and opportunities to learning processes and outcomes depending on learner characteristics and instructional supports. In this experimental study, we examined how one such HLE--MetaTutor, an intelligent, multi-agent tutoring system designed to scaffold cognitive and…

Causal Model Progressions as a Foundation for Intelligent Learning Environments.

DTIC Science & Technology

1987-11-01

Foundation for Intelligent Learning Environments 3Barbara Y. White and John R. Frederiksen ~DTIC Novemr1987 ELECTE November1987 JUNO 9 88 Approved I )’I...Learning Environments 12. PERSONAL AUTHOR(S? Barbara Y. White and John R. Frederiksen 13a. TYPE OF REPORT 13b TIME COVERED 14. DATE OF REPORT (Year...architecture of a new type of learning environment that incorporates features of microworlds and of intelligent tutorng systems. The environment is based on

Intelligent fault-tolerant controllers

NASA Technical Reports Server (NTRS)

Huang, Chien Y.

1987-01-01

A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Lessons learned in the development of the STOL intelligent tutoring system

NASA Technical Reports Server (NTRS)

Seamster, Thomas; Baker, Clifford; Ames, Troy

1991-01-01

Lessons learned during the development of the NASA Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS), being developed at NASA Goddard Space Flight Center are presented. The purpose of the intelligent tutor is to train STOL users by adapting tutoring based on inferred student strengths and weaknesses. This system has been under development for over one year and numerous lessons learned have emerged. These observations are presented in three sections, as follows. The first section addresses the methodology employed in the development of the STOL ITS and briefly presents the ITS architecture. The second presents lessons learned, in the areas of: intelligent tutor development; documentation and reporting; cost and schedule control; and tools and shells effectiveness. The third section presents recommendations which may be considered by other ITS developers, addressing: access, use and selection of subject matter experts; steps involved in ITS development; use of ITS interface design prototypes as part of knowledge engineering; and tools and shells effectiveness.

Generalizing on Multiple Grounds: Performance Learning in Model-Based Troubleshooting

DTIC Science & Technology

1989-02-01

Aritificial Intelligence , 24, 1984. [Ble88] Guy E. Blelloch. Scan Primitives and Parallel Vector Models. PhD thesis, Artificial Intelligence Laboratory...Diagnostic reasoning based on strcture and behavior. Aritificial Intelligence , 24, 1984. [dK86] J. de Kleer. An assumption-based truth maintenance system...diagnosis. Aritificial Intelligence , 24. �. )3 94 BIBLIOGRAPHY [Ham87] Kristian J. Hammond. Learning to anticipate and avoid planning prob- lems

ElectronixTutor: An Intelligent Tutoring System with Multiple Learning Resources for Electronics

ERIC Educational Resources Information Center

Graesser, Arthur C.; Hu, Xiangen; Nye, Benjamin D.; VanLehn, Kurt; Kumar, Rohit; Heffernan, Cristina; Heffernan, Neil; Woolf, Beverly; Olney, Andrew M.; Rus, Vasile; Andrasik, Frank; Pavlik, Philip; Cai, Zhiqiang; Wetzel, Jon; Morgan, Brent; Hampton, Andrew J.; Lippert, Anne M.; Wang, Lijia; Cheng, Qinyu; Vinson, Joseph E.; Kelly, Craig N.; McGlown, Cadarrius; Majmudar, Charvi A.; Morshed, Bashir; Baer, Whitney

2018-01-01

Background: The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics,…

Agents Control in Intelligent Learning Systems: The Case of Reactive Characteristics

ERIC Educational Resources Information Center

Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; de Arriaga, Fernando; Escarela-Perez, Rafael

2006-01-01

Intelligent learning systems (ILSs) have evolved in the last few years basically because of influences received from multi-agent architectures (MAs). Conflict resolution among agents has been a very important problem for multi-agent systems, with specific features in the case of ILSs. The literature shows that ILSs with cognitive or pedagogical…

Help Helps, but Only so Much: Research on Help Seeking with Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R.

2016-01-01

Help seeking is an important process in self-regulated learning (SRL). It may influence learning with intelligent tutoring systems (ITSs), because many ITSs provide help, often at the student's request. The Help Tutor was a tutor agent that gave in-context, real-time feedback on students' help-seeking behavior, as they were learning with an ITS.…

Web-based e-learning and virtual lab of human-artificial immune system.

PubMed

Gong, Tao; Ding, Yongsheng; Xiong, Qin

2014-05-01

Human immune system is as important in keeping the body healthy as the brain in supporting the intelligence. However, the traditional models of the human immune system are built on the mathematics equations, which are not easy for students to understand. To help the students to understand the immune systems, a web-based e-learning approach with virtual lab is designed for the intelligent system control course by using new intelligent educational technology. Comparing the traditional graduate educational model within the classroom, the web-based e-learning with the virtual lab shows the higher inspiration in guiding the graduate students to think independently and innovatively, as the students said. It has been found that this web-based immune e-learning system with the online virtual lab is useful for teaching the graduate students to understand the immune systems in an easier way and design their simulations more creatively and cooperatively. The teaching practice shows that the optimum web-based e-learning system can be used to increase the learning effectiveness of the students.

Intelligent Systems and Its Applications in Robotics

NASA Astrophysics Data System (ADS)

Kaynak, Okyay

The last decade of the last millennium is characterized by what might be called the intelligent systems revolution, as a result of which, it is now possible to have man made systems that exhibit ability to reason, learn from experience and make rational decisions without human intervention. Prof. Zadeh has coined the word MIQ (machine intelligence quotient) to describe a measure of intelligence of man-made systems. In this perspective, an intelligent system can be defined as a system that has a high MIQ.

Machine Learning-based Intelligent Formal Reasoning and Proving System

NASA Astrophysics Data System (ADS)

Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

2018-03-01

The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

An intelligent robotic aid system for human services

NASA Technical Reports Server (NTRS)

Kawamura, K.; Bagchi, S.; Iskarous, M.; Pack, R. T.; Saad, A.

1994-01-01

The long term goal of our research at the Intelligent Robotic Laboratory at Vanderbilt University is to develop advanced intelligent robotic aid systems for human services. As a first step toward our goal, the current thrusts of our R&D are centered on the development of an intelligent robotic aid called the ISAC (Intelligent Soft Arm Control). In this paper, we describe the overall system architecture and current activities in intelligent control, adaptive/interactive control and task learning.

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

Stupid Tutoring Systems, Intelligent Humans

ERIC Educational Resources Information Center

Baker, Ryan S.

2016-01-01

The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…

Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

PubMed

Oudeyer, Pierre-Yves

2017-01-01

Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.

Educational Assessment via a Web-Based Intelligent System

ERIC Educational Resources Information Center

Huang, Jingshan; He, Lei; Davidson-Shivers, Gayle V.

2011-01-01

Effective assessment is vital in educational activities. We propose IWAS (intelligent Web-based assessment system), an intelligent, generalized and real-time system to assess both learning and teaching. IWAS provides a foundation for more efficiency in instructional activities and, ultimately, students' performances. Our contributions are…

Automated expert modeling for automated student evaluation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abbott, Robert G.

The 8th International Conference on Intelligent Tutoring Systems provides a leading international forum for the dissemination of original results in the design, implementation, and evaluation of intelligent tutoring systems and related areas. The conference draws researchers from a broad spectrum of disciplines ranging from artificial intelligence and cognitive science to pedagogy and educational psychology. The conference explores intelligent tutoring systems increasing real world impact on an increasingly global scale. Improved authoring tools and learning object standards enable fielding systems and curricula in real world settings on an unprecedented scale. Researchers deploy ITS's in ever larger studies and increasingly use datamore » from real students, tasks, and settings to guide new research. With high volumes of student interaction data, data mining, and machine learning, tutoring systems can learn from experience and improve their teaching performance. The increasing number of realistic evaluation studies also broaden researchers knowledge about the educational contexts for which ITS's are best suited. At the same time, researchers explore how to expand and improve ITS/student communications, for example, how to achieve more flexible and responsive discourse with students, help students integrate Web resources into learning, use mobile technologies and games to enhance student motivation and learning, and address multicultural perspectives.« less

Facts and fiction of learning systems. [decision making intelligent control

NASA Technical Reports Server (NTRS)

Saridis, G. N.

1975-01-01

The methodology that will provide the updated precision for the hardware control and the advanced decision making and planning in the software control is called learning systems and intelligent control. It was developed theoretically as an alternative for the nonsystematic heuristic approaches of artificial intelligence experiments and the inflexible formulation of modern optimal control methods. Its basic concepts are discussed and some feasibility studies of some practical applications are presented.

Generalizing Automated Detection of the Robustness of Student Learning in an Intelligent Tutor for Genetics

ERIC Educational Resources Information Center

Baker, Ryan S. J. d.; Corbett, Albert T.; Gowda, Sujith M.

2013-01-01

Recently, there has been growing emphasis on supporting robust learning within intelligent tutoring systems, assessed by measures such as transfer to related skills, preparation for future learning, and longer term retention. It has been shown that different pedagogical strategies promote robust learning to different degrees. However, the student…

Encouraging Student Reflection and Articulation Using a Learning Companion: A Commentary

ERIC Educational Resources Information Center

Goodman, Bradley; Linton, Frank; Gaimari, Robert

2016-01-01

Our 1998 paper "Encouraging Student Reflection and Articulation using a Learning Companion" (Goodman et al. 1998) was a stepping stone in the progression of learning companions for intelligent tutoring systems (ITS). A simulated learning companion, acting as a peer in an intelligent tutoring environment ensures the availability of a…

Artificial intelligence: Learning to see and act

NASA Astrophysics Data System (ADS)

Schölkopf, Bernhard

2015-02-01

An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

What Are Intellectual and Developmental Disabilities (IDDs)?

MedlinePlus

... characterized by problems with both: Intellectual functioning or intelligence, which include the ability to learn, reason, problem ... cord, and nervous system function, which can affect intelligence and learning. These conditions can also cause other ...

Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

ERIC Educational Resources Information Center

Yaratan, Huseyin

2003-01-01

An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

Implementation and Performance Evaluation of Parameter Improvement Mechanisms for Intelligent E-Learning Systems

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chu, San-Shine; Guan, Chih-Tai

2007-01-01

In recent years, designing useful learning diagnosis systems has become a hot research topic in the literature. In order to help teachers easily analyze students' profiles in intelligent tutoring system, it is essential that students' portfolios can be transformed into some useful information to reflect the extent of students' participation in the…

Learning from Multiple Collaborating Intelligent Tutors: An Agent-based Approach.

ERIC Educational Resources Information Center

Solomos, Konstantinos; Avouris, Nikolaos

1999-01-01

Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)

Survey on Intelligent Assistance for Workplace Learning in Software Engineering

NASA Astrophysics Data System (ADS)

Ras, Eric; Rech, Jörg

Technology-enhanced learning (TEL) systems and intelligent assistance systems aim at supporting software engineers during learning and work. A questionnaire-based survey with 89 responses from industry was conducted to find out what kinds of services should be provided and how, as well as to determine which software engineering phases they should focus on. In this paper, we present the survey results regarding intelligent assistance for workplace learning in software engineering. We analyzed whether specific types of assistance depend on the organization's size, the respondent's role, and the experience level. The results show a demand for TEL that supports short-term problem solving and long-term competence development at the workplace.

The Convergence of Intelligences

NASA Astrophysics Data System (ADS)

Diederich, Joachim

Minsky (1985) argued an extraterrestrial intelligence may be similar to ours despite very different origins. ``Problem- solving'' offers evolutionary advantages and individuals who are part of a technical civilisation should have this capacity. On earth, the principles of problem-solving are the same for humans, some primates and machines based on Artificial Intelligence (AI) techniques. Intelligent systems use ``goals'' and ``sub-goals'' for problem-solving, with memories and representations of ``objects'' and ``sub-objects'' as well as knowledge of relations such as ``cause'' or ``difference.'' Some of these objects are generic and cannot easily be divided into parts. We must, therefore, assume that these objects and relations are universal, and a general property of intelligence. Minsky's arguments from 1985 are extended here. The last decade has seen the development of a general learning theory (``computational learning theory'' (CLT) or ``statistical learning theory'') which equally applies to humans, animals and machines. It is argued that basic learning laws will also apply to an evolved alien intelligence, and this includes limitations of what can be learned efficiently. An example from CLT is that the general learning problem for neural networks is intractable, i.e. it cannot be solved efficiently for all instances (it is ``NP-complete''). It is the objective of this paper to show that evolved intelligences will be constrained by general learning laws and will use task-decomposition for problem-solving. Since learning and problem-solving are core features of intelligence, it can be said that intelligences converge despite very different origins.

Intelligent Counseling System: A 24 x 7 Academic Advisor

ERIC Educational Resources Information Center

Leung, Chun Ming; Tsang, Eva Y. M.; Lam, S. S.; Pang, Dominic C. W.

2010-01-01

Universities are increasingly looking into self-service systems with intelligent digital agents to supplement or replace labor-intensive services, such as academic counseling. The Open University of Hong Kong has developed an intelligent online system that instantly responds to enquiries about career development, learning modes, program/course…

Developing Adaptive and Intelligent Tutoring Systems (AITS): A General Framework and Its Implementations

ERIC Educational Resources Information Center

Hafidi, Mohamed; Bensebaa, Tahar

2014-01-01

Several adaptive and intelligent tutoring systems (AITS) have been developed with different variables. These variables were the cognitive traits, cognitive styles, and learning behavior. However, these systems neglect the importance of the learner's multiple intelligences, the learner's skill level and the learner's feedback when implementing…

Implications for Intelligent Tutoring Systems for Research and Practice in Foreign Language Learning, NFLC Occasional Papers.

ERIC Educational Resources Information Center

Ginsberg, Ralph B.

Most of the now commonplace computer-assisted instruction (CAI) uses computers to increase the capacity to perform logical, numerical, and symbolic computations. However, computers are an interactive and potentially intelligent medium. The implications of artificial intelligence (AI) for learning are more radical than those for traditional CAI. AI…

On Using Intelligent Computer-Assisted Language Learning in Real-Life Foreign Language Teaching and Learning

ERIC Educational Resources Information Center

Amaral, Luiz A.; Meurers, Detmar

2011-01-01

This paper explores the motivation and prerequisites for successful integration of Intelligent Computer-Assisted Language Learning (ICALL) tools into current foreign language teaching and learning (FLTL) practice. We focus on two aspects, which we argue to be important for effective ICALL system development and use: (i) the relationship between…

The Social Semantic Web in Intelligent Learning Environments: State of the Art and Future Challenges

ERIC Educational Resources Information Center

Jovanovic, Jelena; Gasevic, Dragan; Torniai, Carlo; Bateman, Scott; Hatala, Marek

2009-01-01

Today's technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments…

The Intelligent Technologies of Electronic Information System

NASA Astrophysics Data System (ADS)

Li, Xianyu

2017-08-01

Based upon the synopsis of system intelligence and information services, this paper puts forward the attributes and the logic structure of information service, sets forth intelligent technology framework of electronic information system, and presents a series of measures, such as optimizing business information flow, advancing data decision capability, improving information fusion precision, strengthening deep learning application and enhancing prognostic and health management, and demonstrates system operation effectiveness. This will benefit the enhancement of system intelligence.

Intelligent Tutoring Systems by and for the Developing World: A Review of Trends and Approaches for Educational Technology in a Global Context

ERIC Educational Resources Information Center

Nye, Benjamin D.

2015-01-01

As information and communication technology access expands in the developing world, learning technologies have the opportunity to play a growing role to enhance and supplement strained educational systems. Intelligent tutoring systems (ITS) offer strong learning gains, but are a class of technology traditionally designed for most-developed…

Increasing Parent Engagement in Student Learning Using an Intelligent Tutoring System

ERIC Educational Resources Information Center

Broderick, Zachary; O'Connor, Christine; Mulcahy, Courtney; Heffernan, Neil; Heffernan, Christina

2011-01-01

This study demonstrates the ability of an Intelligent Tutoring System (ITS) to increase parental engagement in student learning. A parent notification feature was developed for the web-based ASSISTment ITS that allows parents to log into their own accounts and access detailed data about their students' performance. Parents from a local middle…

Does It Really Matter whether Students' Contributions Are Spoken versus Typed in an Intelligent Tutoring System with Natural Language?

ERIC Educational Resources Information Center

D'Mello, Sidney K.; Dowell, Nia; Graesser, Arthur

2011-01-01

There is the question of whether learning differs when students speak versus type their responses when interacting with intelligent tutoring systems with natural language dialogues. Theoretical bases exist for three contrasting hypotheses. The "speech facilitation" hypothesis predicts that spoken input will "increase" learning,…

Investigating Effects of Embedding Collaboration in an Intelligent Tutoring System for Elementary School Students

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent

2016-01-01

Intelligent Tutoring Systems (ITSs) are beneficial for individual students learning in several domains, including mathematics where they have been used to support both secondary and elementary students. Collaborative learning may be beneficial to include in ITSs, particularly for conceptual knowledge. There is little work on collaborative ITSs,…

Intelligent Tutoring Systems for Collaborative Learning: Enhancements to Authoring Tools

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol

2013-01-01

Collaborative and individual instruction may support different types of knowledge. Optimal instruction for a subject domain may therefore need to combine these two modes of instruction. There has not been much research, however, on combining individual and collaborative learning with Intelligent Tutoring Systems (ITSs). A first step is to expand…

A Mixed-Response Intelligent Tutoring System Based on Learning from Demonstration

ERIC Educational Resources Information Center

Alvarez Xochihua, Omar

2012-01-01

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

Authoring Tools for Collaborative Intelligent Tutoring System Environments

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael

2014-01-01

Authoring tools have been shown to decrease the amount of time and resources needed for the development of Intelligent Tutoring Systems (ITSs). Although collaborative learning has been shown to be beneficial to learning, most of the current authoring tools do not support the development of collaborative ITSs. In this paper, we discuss an extension…

Machine Methods for Acquiring, Learning, and Applying Knowledge.

ERIC Educational Resources Information Center

Hayes-Roth, Frederick; And Others

A research plan for identifying and acting upon constraints that impede the development of knowledge-based intelligent systems is described. The two primary problems identified are knowledge programming, the task of which is to create an intelligent system that does what an expert says it should, and learning, the problem requiring the criticizing…

An E-learning System based on Affective Computing

NASA Astrophysics Data System (ADS)

Duo, Sun; Song, Lu Xue

In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

PubMed

Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

2014-12-01

This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club.

ERIC Educational Resources Information Center

Chan, Tak-Wai

1996-01-01

Describes the development of learning companion systems and their contributions to the class of social learning systems that integrate artificial intelligence agents and use machine learning to tutor and interact with students. Outlines initial social learning projects, their programming languages, and weakness. Future improvements will include…

Artificial Intelligence Measurement System, Overview and Lessons Learned. Final Project Report.

ERIC Educational Resources Information Center

Baker, Eva L.; Butler, Frances A.

This report summarizes the work conducted for the Artificial Intelligence Measurement System (AIMS) Project which was undertaken as an exploration of methodology to consider how the effects of artificial intelligence systems could be compared to human performance. The research covered four areas of inquiry: (1) natural language processing and…

Active learning machine learns to create new quantum experiments.

PubMed

Melnikov, Alexey A; Poulsen Nautrup, Hendrik; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J

2018-02-06

How useful can machine learning be in a quantum laboratory? Here we raise the question of the potential of intelligent machines in the context of scientific research. A major motivation for the present work is the unknown reachability of various entanglement classes in quantum experiments. We investigate this question by using the projective simulation model, a physics-oriented approach to artificial intelligence. In our approach, the projective simulation system is challenged to design complex photonic quantum experiments that produce high-dimensional entangled multiphoton states, which are of high interest in modern quantum experiments. The artificial intelligence system learns to create a variety of entangled states and improves the efficiency of their realization. In the process, the system autonomously (re)discovers experimental techniques which are only now becoming standard in modern quantum optical experiments-a trait which was not explicitly demanded from the system but emerged through the process of learning. Such features highlight the possibility that machines could have a significantly more creative role in future research.

A Proposed Intelligent Policy-Based Interface for a Mobile eHealth Environment

NASA Astrophysics Data System (ADS)

Tavasoli, Amir; Archer, Norm

Users of mobile eHealth systems are often novices, and the learning process for them may be very time consuming. In order for systems to be attractive to potential adopters, it is important that the interface should be very convenient and easy to learn. However, the community of potential users of a mobile eHealth system may be quite varied in their requirements, so the system must be able to adapt easily to suit user preferences. One way to accomplish this is to have the interface driven by intelligent policies. These policies can be refined gradually, using inputs from potential users, through intelligent agents. This paper develops a framework for policy refinement for eHealth mobile interfaces, based on dynamic learning from user interactions.

An Approach to Building a Learning Management System that Emphasizes on Incorporating Individualized Dissemination with Intelligent Tutoring

NASA Astrophysics Data System (ADS)

Ghosh, Sreya

2017-02-01

This article proposes a new six-model architecture for an intelligent tutoring system to be incorporated in a learning management system with domain-independence feature and individualized dissemination. The present six model architecture aims to simulate a human tutor. Some recent extensions of using intelligent tutoring system (ITS) explores learning management systems to behave as a real teacher during a teaching-learning process, by taking care of, mainly, the dynamic response system. However, the present paper argues that to mimic a human teacher it needs not only the dynamic response but also the incorporation of the teacher's dynamic review of students' performance and keeping track of their current level of understanding. Here, the term individualization has been used to refer to tailor making of contents and its dissemination fitting to the individual needs and capabilities of learners who is taking a course online and is subjected to teaching in absentia. This paper describes how the individual models of the proposed architecture achieves the features of ITS.

The application of multiple intelligence approach to the learning of human circulatory system

NASA Astrophysics Data System (ADS)

Kumalasari, Lita; Yusuf Hilmi, A.; Priyandoko, Didik

2017-11-01

The purpose of this study is to offer an alternative teaching approach or strategies which able to accommodate students’ different ability, intelligence and learning style. Also can gives a new idea for the teacher as a facilitator for exploring how to teach the student in creative ways and more student-center activities, for a lesson such as circulatory system. This study was carried out at one private school in Bandung involved eight students to see their responses toward the lesson that delivered by using Multiple Intelligence approach which is include Linguistic, Logical-Mathematical, Visual-Spatial, Musical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Naturalistic. Students were test by using MI test based on Howard Gardner’s MI model to see their dominant intelligence. The result showed the percentage of top three ranks of intelligence are Bodily-Kinesthetic (73%), Visual-Spatial (68%), and Logical-Mathematical (61%). The learning process is given by using some different multimedia and activities to engaged their learning style and intelligence such as mini experiment, short clip, and questions. Student response is given by using self-assessment and the result is all students said the lesson gives them a knowledge and skills that useful for their life, they are clear with the explanation given, they didn’t find difficulties to understand the lesson and can complete the assignment given. At the end of the study, it is reveal that the students who are learned by Multiple Intelligence instructional approach have more enhance to the lesson given. It’s also found out that the students participated in the learning process which Multiple Intelligence approach was applied enjoyed the activities and have great fun.

Intelligent Web-Based Learning System with Personalized Learning Path Guidance

ERIC Educational Resources Information Center

Chen, C. M.

2008-01-01

Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

1988-01-01

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

1988-01-01

In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

A Meta-Analysis of the Effectiveness of Intelligent Tutoring Systems on College Students' Academic Learning

ERIC Educational Resources Information Center

Steenbergen-Hu, Saiying; Cooper, Harris

2014-01-01

This meta-analysis synthesizes research on the effectiveness of intelligent tutoring systems (ITS) for college students. Thirty-five reports were found containing 39 studies assessing the effectiveness of 22 types of ITS in higher education settings. Most frequently studied were AutoTutor, Assessment and Learning in Knowledge Spaces, eXtended…

Knowledge Based Artificial Augmentation Intelligence Technology: Next Step in Academic Instructional Tools for Distance Learning

ERIC Educational Resources Information Center

Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh

2017-01-01

With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…

Artificial Intelligence--Applications in Education.

ERIC Educational Resources Information Center

Poirot, James L.; Norris, Cathleen A.

1987-01-01

This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

Integrating Human and Computer Intelligence. Technical Report No. 32.

ERIC Educational Resources Information Center

Pea, Roy D.

This paper explores the thesis that advances in computer applications and artificial intelligence have important implications for the study of development and learning in psychology. Current approaches to the use of computers as devices for problem solving, reasoning, and thinking--i.e., expert systems and intelligent tutoring systems--are…

Designing a holistic end-to-end intelligent network analysis and security platform

NASA Astrophysics Data System (ADS)

Alzahrani, M.

2018-03-01

Firewall protects a network from outside attacks, however, once an attack entering a network, it is difficult to detect. Recent significance accidents happened. i.e.: millions of Yahoo email account were stolen and crucial data from institutions are held for ransom. Within two year Yahoo’s system administrators were not aware that there are intruder inside the network. This happened due to the lack of intelligent tools to monitor user behaviour in internal network. This paper discusses a design of an intelligent anomaly/malware detection system with proper proactive actions. The aim is to equip the system administrator with a proper tool to battle the insider attackers. The proposed system adopts machine learning to analyse user’s behaviour through the runtime behaviour of each node in the network. The machine learning techniques include: deep learning, evolving machine learning perceptron, hybrid of Neural Network and Fuzzy, as well as predictive memory techniques. The proposed system is expanded to deal with larger network using agent techniques.

Adaptive Intelligent Support to Improve Peer Tutoring in Algebra

ERIC Educational Resources Information Center

Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R.

2014-01-01

Adaptive collaborative learning support (ACLS) involves collaborative learning environments that adapt their characteristics, and sometimes provide intelligent hints and feedback, to improve individual students' collaborative interactions. ACLS often involves a system that can automatically assess student dialogue, model effective and…

Intelligent power management in a vehicular system with multiple power sources

NASA Astrophysics Data System (ADS)

Murphey, Yi L.; Chen, ZhiHang; Kiliaris, Leonidas; Masrur, M. Abul

This paper presents an optimal online power management strategy applied to a vehicular power system that contains multiple power sources and deals with largely fluctuated load requests. The optimal online power management strategy is developed using machine learning and fuzzy logic. A machine learning algorithm has been developed to learn the knowledge about minimizing power loss in a Multiple Power Sources and Loads (M_PS&LD) system. The algorithm exploits the fact that different power sources used to deliver a load request have different power losses under different vehicle states. The machine learning algorithm is developed to train an intelligent power controller, an online fuzzy power controller, FPC_MPS, that has the capability of finding combinations of power sources that minimize power losses while satisfying a given set of system and component constraints during a drive cycle. The FPC_MPS was implemented in two simulated systems, a power system of four power sources, and a vehicle system of three power sources. Experimental results show that the proposed machine learning approach combined with fuzzy control is a promising technology for intelligent vehicle power management in a M_PS&LD power system.

Analyzing User Interaction to Design an Intelligent e-Learning Environment

ERIC Educational Resources Information Center

Sharma, Richa

2011-01-01

Building intelligent course designing systems adaptable to the learners' needs is one of the key goals of research in e-learning. This goal is all the more crucial as gaining knowledge in an e-learning environment depends solely on computer mediated interaction within the learner group and among the learners and instructors. The patterns generated…

Effects of Prior Knowledge in Mathematics on Learner-Interface Interactions in a Learning-by-Teaching Intelligent Tutoring System

ERIC Educational Resources Information Center

Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T.

2016-01-01

This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…

Intelligent Learning System using cognitive science theory and artificial intelligence methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cristensen, D.L.

1986-01-01

This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic ismore » used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.« less

Man-Robot Symbiosis: A Framework For Cooperative Intelligence And Control

NASA Astrophysics Data System (ADS)

Parker, Lynne E.; Pin, Francois G.

1988-10-01

The man-robot symbiosis concept has the fundamental objective of bridging the gap between fully human-controlled and fully autonomous systems to achieve true man-robot cooperative control and intelligence. Such a system would allow improved speed, accuracy, and efficiency of task execution, while retaining the man in the loop for innovative reasoning and decision-making. The symbiont would have capabilities for supervised and unsupervised learning, allowing an increase of expertise in a wide task domain. This paper describes a robotic system architecture facilitating the symbiotic integration of teleoperative and automated modes of task execution. The architecture reflects a unique blend of many disciplines of artificial intelligence into a working system, including job or mission planning, dynamic task allocation, man-robot communication, automated monitoring, and machine learning. These disciplines are embodied in five major components of the symbiotic framework: the Job Planner, the Dynamic Task Allocator, the Presenter/Interpreter, the Automated Monitor, and the Learning System.

Bibliography: Artificial Intelligence.

ERIC Educational Resources Information Center

Smith, Richard L.

1986-01-01

Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

Intelligent transportation systems benefits, costs, and lessons learned : 2014 update report.

DOT National Transportation Integrated Search

2014-06-01

Intelligent transportation systems (ITS) provide a proven set of strategies for advancing transportation safety, mobility, and environmental sustainability by integrating communication and information technology applications into the management and o...

Substructure Discovery of Macro-Operators

DTIC Science & Technology

1988-05-01

Aspects of Scientific Discovery," in Machine Learning: An Artifcial Intelligence Approach, Vol. II. R. S. Michalski, J. G. Carbonell and T. M. Mitchell (ed... intelligent robot using this system could learn how to perform new tasks by watching tasks being performed by someone else. even if the robot does not possess...Substructure Discovery of Macro-Operators* Bradley L. Whitehall Artificial Intelligence Research Group Coordinated Science Laboratory ’University of Illinois at

An Intelligent Information Access System Assisting a Case Based Learning Methodology Evaluated in Higher Education with Medical Students

ERIC Educational Resources Information Center

Aparicio, Fernando; De Buenaga, Manuel; Rubio, Margarita; Hernando, Asuncion

2012-01-01

In recent years there has been a shift in educational methodologies toward a student-centered approach, one which increasingly emphasizes the integration of computer tools and intelligent systems adopting different roles. In this paper we describe in detail the development of an Intelligent Information Access system used as the basis for producing…

A Flowchart-Based Intelligent Tutoring System for Improving Problem-Solving Skills of Novice Programmers

ERIC Educational Resources Information Center

Hooshyar, D.; Ahmad, R. B.; Yousefi, M.; Yusop, F. D.; Horng, S.-J.

2015-01-01

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem-solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one-to-one personalized and…

Smart-system of distance learning of visually impaired people based on approaches of artificial intelligence

NASA Astrophysics Data System (ADS)

Samigulina, Galina A.; Shayakhmetova, Assem S.

2016-11-01

Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.

Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

PubMed

Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

2007-01-01

Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

Experiential Learning Using QlikView Business Intelligence Software

ERIC Educational Resources Information Center

Podeschi, R. J.

2015-01-01

This paper reports on the use of QlikView business intelligence software for use in a Business Intelligence (BI) course within an undergraduate information systems program. The course provides students with concepts related to data warehousing, data mining, visualizations, and software tools to provide business intelligence solutions for decision…

Conversational Simulation in Computer-Assisted Language Learning: Potential and Reality.

ERIC Educational Resources Information Center

Coleman, D. Wells

1988-01-01

Addresses the potential of conversational simulations for computer-assisted language learning (CALL) and reasons why this potential is largely untapped. Topics discussed include artificial intelligence; microworlds; parsing; realism versus reality in computer software; intelligent tutoring systems; and criteria to clarify what kinds of CALL…

Does Supporting Multiple Student Strategies Lead to Greater Learning and Motivation? Investigating a Source of Complexity in the Architecture of Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Waalkens, Maaike; Aleven, Vincent; Taatgen, Niels

2013-01-01

Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem. But does greater freedom mean that students…

The Effects of Self-Regulatory Learning through Computer-Assisted Intelligent Tutoring System on the Improvement of EFL Learners' Speaking Ability

ERIC Educational Resources Information Center

Mohammadzadeh, Ahmad; Sarkhosh, Mehdi

2018-01-01

The current study attempted to investigate the effects of self-regulatory learning through computer-assisted intelligent tutoring system on the improvement of speaking ability. The participants of the study, who spoke Azeri Turkish as their mother tongue, were students of Applied Linguistics at BA level at Pars Abad's Azad University, Ardebil,…

Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jha, Sumit Kumar; Pullum, Laura L; Ramanathan, Arvind

Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studyingmore » the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.« less

Toward Intelligent Machine Learning Algorithms

DTIC Science & Technology

1988-05-01

Machine learning is recognized as a tool for improving the performance of many kinds of systems, yet most machine learning systems themselves are not...directed systems, and with the addition of a knowledge store for organizing and maintaining knowledge to assist learning, a learning machine learning (L...ML) algorithm is possible. The necessary components of L-ML systems are presented along with several case descriptions of existing machine learning systems

Design and Control of Large Collections of Learning Agents

NASA Technical Reports Server (NTRS)

Agogino, Adrian

2001-01-01

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

Developing Emotion-Aware, Advanced Learning Technologies: A Taxonomy of Approaches and Features

ERIC Educational Resources Information Center

Harley, Jason M.; Lajoie, Susanne P.; Frasson, Claude; Hall, Nathan C.

2017-01-01

A growing body of work on intelligent tutoring systems, affective computing, and artificial intelligence in education is exploring creative, technology-driven approaches to enhance learners' experience of adaptive, positively-valenced emotions while interacting with advanced learning technologies. Despite this, there has been no published work to…

Does Artificial Tutoring Foster Inquiry Based Learning?

ERIC Educational Resources Information Center

Schmoelz, Alexander; Swertz, Christian; Forstner, Alexandra; Barberi, Alessandro

2014-01-01

This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based…

Knowledge-Based Systems Research

DTIC Science & Technology

1990-08-24

P. S., Laird, J. E., Newell, A. and McCarl, R. 1991. A Preliminary Analysis of the SOAR Architecture as a Basis for General Intelligence . Artifcial ...on reverse of neceSSjr’y gnd identify by block nhmber) FIELD I GRO’= SUB-C.OROUC Artificial Intelligence , Blackboard Systems, U°nstraint Satisfaction...knowledge acquisition; symbolic simulation; logic-based systems with self-awareness; SOAR, an architecture for general intelligence and learning

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

A Multi-Agent System for Intelligent Online Education.

ERIC Educational Resources Information Center

O'Riordan, Colm; Griffith, Josephine

1999-01-01

Describes the system architecture of an intelligent Web-based education system that includes user modeling agents, information filtering agents for automatic information gathering, and the multi-agent interaction. Discusses information management; user interaction; support for collaborative peer-peer learning; implementation; testing; and future…

Intelligent transportation systems benefits, costs, and lessons learned : 2005 update

DOT National Transportation Integrated Search

2005-05-01

Intelligent Transportation Systems (ITS) technologies offer a clear opportunity to improve transportation safety, relieve congestion, and enhance productivity. This report is a continuation of a series of reports providing a synthesis of the informat...

Intelligent mobility research for robotic locomotion in complex terrain

NASA Astrophysics Data System (ADS)

Trentini, Michael; Beckman, Blake; Digney, Bruce; Vincent, Isabelle; Ricard, Benoit

2006-05-01

The objective of the Autonomous Intelligent Systems Section of Defence R&D Canada - Suffield is best described by its mission statement, which is "to augment soldiers and combat systems by developing and demonstrating practical, cost effective, autonomous intelligent systems capable of completing military missions in complex operating environments." The mobility requirement for ground-based mobile systems operating in urban settings must increase significantly if robotic technology is to augment human efforts in these roles and environments. The intelligence required for autonomous systems to operate in complex environments demands advances in many fields of robotics. This has resulted in large bodies of research in areas of perception, world representation, and navigation, but the problem of locomotion in complex terrain has largely been ignored. In order to achieve its objective, the Autonomous Intelligent Systems Section is pursuing research that explores the use of intelligent mobility algorithms designed to improve robot mobility. Intelligent mobility uses sensing, control, and learning algorithms to extract measured variables from the world, control vehicle dynamics, and learn by experience. These algorithms seek to exploit available world representations of the environment and the inherent dexterity of the robot to allow the vehicle to interact with its surroundings and produce locomotion in complex terrain. The primary focus of the paper is to present the intelligent mobility research within the framework of the research methodology, plan and direction defined at Defence R&D Canada - Suffield. It discusses the progress and future direction of intelligent mobility research and presents the research tools, topics, and plans to address this critical research gap. This research will create effective intelligence to improve the mobility of ground-based mobile systems operating in urban settings to assist the Canadian Forces in their future urban operations.

An Intelligent E-Learning System Based on Learner Profiling and Learning Resources Adaptation

ERIC Educational Resources Information Center

Tzouveli, Paraskevi; Mylonas, Phivos; Kollias, Stefanos

2008-01-01

Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…

Enhancing an adaptive e-learning system with didactic test assessment using an expert system

NASA Astrophysics Data System (ADS)

Bradáč, Vladimír; Kostolányová, Kateřina

2017-07-01

The paper deals with a follow-up research on intelligent tutoring systems that were studied in authors' previous papers from the point of view of describing their advantages. In this paper, the authors make use of the fuzzy logic expert system, which assesses student's knowledge, and integrate it into the intelligent tutoring system called Barborka. The goal is to create an even more personal student's study plan, which is tailored both to student's sensory/learning preferences and the level of knowledge of the given subject.

Evolution of intelligent transportation systems for mobility management and coordination serving California's rural frontier.

DOT National Transportation Integrated Search

2012-01-01

This report documents the evolution, development, and lessons learned while attempting to identify, modify, and deploy Intelligent Transportation System (ITS) and advanced technology tools to facilitate coordination of public transit and social (huma...

Intelligent flight control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1993-01-01

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.

Dynamic Learning Style Prediction Method Based on a Pattern Recognition Technique

ERIC Educational Resources Information Center

Yang, Juan; Huang, Zhi Xing; Gao, Yue Xiang; Liu, Hong Tao

2014-01-01

During the past decade, personalized e-learning systems and adaptive educational hypermedia systems have attracted much attention from researchers in the fields of computer science Aand education. The integration of learning styles into an intelligent system is a possible solution to the problems of "learning deviation" and…

Exploring Moodle Functionality for Managing Open Distance Learning E-Assessments

ERIC Educational Resources Information Center

Koneru, Indira

2017-01-01

Current and emerging technologies enable Open Distance Learning (ODL) institutions integrate e-Learning in innovative ways and add value to the existing teaching-learning and assessment processes. ODL e-Assessment systems have evolved from Computer Assisted/Aided Assessment (CAA) systems through intelligent assessment and feedback systems.…

Improving Marketing Intelligence through Learning Systems and Knowledge Communities in Not-for-Profit Workplaces

ERIC Educational Resources Information Center

Murray, Peter; Carter, Leanne

2005-01-01

Purpose: The purpose of the paper is to illustrate how marketing intelligence might be improved when an organisation's learning capacity is integrated and incorporated in well-defined organisational subsystems in a not-for-profit context. Design/methodology/approach: First, given that market orientation is primarily concerned with gathering and…

A Semantic Approach to Intelligent and Personal Tutoring System

ERIC Educational Resources Information Center

Sette, Maria

2017-01-01

Cyberlearning presents numerous challenges such as the lack of personal and assessment-driven learning, how students are often puzzled by the lack of instructor guidance and feedback, the huge volume of diverse learning materials, and the inability to zoom in from the general concepts to the more specific ones, or vice versa. Intelligent tutoring…

A Contest-Oriented Project for Learning Intelligent Mobile Robots

ERIC Educational Resources Information Center

Huang, Hsin-Hsiung; Su, Juing-Huei; Lee, Chyi-Shyong

2013-01-01

A contest-oriented project for undergraduate students to learn implementation skills and theories related to intelligent mobile robots is presented in this paper. The project, related to Micromouse, Robotrace (Robotrace is the title of Taiwanese and Japanese robot races), and line-maze contests was developed by the embedded control system research…

Experimental Evaluation of Performance Feedback Using the Dismounted Infantry Virtual After Action Review System. Long Range Navy and Marine Corps Science and Technology Program

DTIC Science & Technology

2007-11-14

Artificial intelligence and 4 23 education , Volume 1: Learning environments and tutoring systems. Hillsdale, NJ: Erlbaum. Wickens, C.D. (1984). Processing...and how to use it to best optimize the learning process. Some researchers (see Loftin & Savely, 1991) have proposed adding intelligent systems to the...is experienced as the cognitive centers in an individual’s brain process visual, tactile, kinesthetic , olfactory, proprioceptive, and auditory

An Intelligent System for Document Retrieval in Distributed Office Environments.

ERIC Educational Resources Information Center

Mukhopadhyay, Uttam; And Others

1986-01-01

MINDS (Multiple Intelligent Node Document Servers) is a distributed system of knowledge-based query engines for efficiently retrieving multimedia documents in an office environment of distributed workstations. By learning document distribution patterns and user interests and preferences during system usage, it customizes document retrievals for…

Fundamentals of the Design and the Operation of an Intelligent Tutoring System for the Learning of the Arithmetical and Algebraic Way of Solving Word Problems

ERIC Educational Resources Information Center

Arnau, David; Arevalillo-Herraez, Miguel; Puig, Luis; Gonzalez-Calero, Jose Antonio

2013-01-01

Designers of interactive learning environments with a focus on word problem solving usually have to compromise between the amount of resolution paths that a user is allowed to follow and the quality of the feedback provided. We have built an intelligent tutoring system (ITS) that is able to both track the user's actions and provide adequate…

Machine learning of parameter control doctrine for sensor and communication systems. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamen, R.B.; Dillard, R.A.

Artificial-intelligence approaches to learning were reviewed for their potential contributions to the construction of a system to learn parameter-control doctrine. Separate learning tasks were isolated and several levels of related problems were distinguished. Formulas for providing the learning system with measures of its performance were derived for four kinds of targets.

Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents

NASA Astrophysics Data System (ADS)

Nguyen, Binh; Skabar, Andrew

In order to overcome the knowledge bottleneck problem, AI researchers have attempted to develop systems that are capable of automated knowledge acquisition. However, learning in these systems is hindered by context (i.e., symbol-grounding) problems, which are caused by the systems lacking the unifying structure of bodies, situations and needs that typify human learning. While the fields of Embodied Artificial Intelligence and Artificial Life have come a long way towards demonstrating how artificial systems can develop knowledge of the physical and social worlds, the focus in these areas has been on low level intelligence, and it is not clear how, such systems can be extended to deal with higher-level knowledge. In this paper, we argue that we can build towards a higher level intelligence by framing the problem as one of stimulating the development of culture and language. Specifically, we identify three important limitations that face the development of culture and language in AI systems, and propose how these limitations can be overcome. We will do this through borrowing ideas from the evolutionary sciences, which have explored how interactions between embodiment and environment have shaped the development of human intelligence and knowledge.

A proposal of an architecture for the coordination level of intelligent machines

NASA Technical Reports Server (NTRS)

Beard, Randall; Farah, Jeff; Lima, Pedro

1993-01-01

The issue of obtaining a practical, structured, and detailed description of an architecture for the Coordination Level of Center for Intelligent Robotic Systems for Sapce Exploration (CIRSSE) Testbed Intelligent Controller is addressed. Previous theoretical and implementation works were the departure point for the discussion. The document is organized as follows: after this introductory section, section 2 summarizes the overall view of the Intelligent Machine (IM) as a control system, proposing a performance measure on which to base its design. Section 3 addresses with some detail implementation issues. An hierarchic petri-net with feedback-based learning capabilities is proposed. Finally, section 4 is an attempt to address the feedback problem. Feedback is used for two functions: error recovery and reinforcement learning of the correct translations for the petri-net transitions.

Adaptive Computerized Instruction.

ERIC Educational Resources Information Center

Ray, Roger D.; And Others

1995-01-01

Describes an artificially intelligent multimedia computerized instruction system capable of developing a conceptual image of what a student is learning while the student is learning it. It focuses on principles of learning and adaptive behavioral control systems theory upon which the system is designed and demonstrates multiple user modes.…

Multi-Armed Bandits for Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Clement, Benjamin; Roy, Didier; Oudeyer, Pierre-Yves; Lopes, Manuel

2015-01-01

We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by students, taking into account the limited time and motivational resources. At a given point in time, the system proposes to the students the activity which makes them progress faster. We introduce two…

A Model for Intelligent Computer-Aided Education Systems.

ERIC Educational Resources Information Center

Du Plessis, Johan P.; And Others

1995-01-01

Proposes a model for intelligent computer-aided education systems that is based on cooperative learning, constructive problem-solving, object-oriented programming, interactive user interfaces, and expert system techniques. Future research is discussed, and a prototype for teaching mathematics to 10- to 12-year-old students is appended. (LRW)

Recent Developments in Interactive and Communicative CALL: Hypermedia and "Intelligent" Systems.

ERIC Educational Resources Information Center

Coughlin, Josette M.

Two recent developments in computer-assisted language learning (CALL), interactive video systems and "intelligent" games, are discussed. Under the first heading, systems combining the use of a computer and video disc player are described, and Compact Discs Interactive (CDI) and Digital Video Interactive (DVI) are reviewed. The…

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Intelligent transportation systems for traffic signal control : deployment benefits and lessons learned

DOT National Transportation Integrated Search

2000-12-01

In this document, a group of authors looks back on the ten years of the national intelligent transportation systems program and examines which ITS technology applications have been successful, which have not been successful, and what are the underlyi...

Not All Wizards Are from Oz: Iterative Design of Intelligent Learning Environments by Communication Capacity Tapering

ERIC Educational Resources Information Center

Mavrikis, Manolis; Gutierrez-Santos, Sergio

2010-01-01

This paper presents a methodology for the design of intelligent learning environments. We recognise that in the educational technology field, theory development and system-design should be integrated and rely on an iterative process that addresses: (a) the difficulty to elicit precise, concise, and operationalized knowledge from "experts" and (b)…

Innovative intelligent technology of distance learning for visually impaired people

NASA Astrophysics Data System (ADS)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.

Intelligent Augmented Reality Training for Motherboard Assembly

ERIC Educational Resources Information Center

Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark

2015-01-01

We investigate the combination of Augmented Reality (AR) with Intelligent Tutoring Systems (ITS) to assist with training for manual assembly tasks. Our approach combines AR graphics with adaptive guidance from the ITS to provide a more effective learning experience. We have developed a modular software framework for intelligent AR training…

Creating Business Intelligence from Course Management Systems

ERIC Educational Resources Information Center

van Dyk, Liezl; Conradie, Pieter

2007-01-01

Purpose: This article seeks to address the interface between individual learning facilitators that use course management systems (CMS) data to support decision-making and course design and institutional infrastructure providers that are responsible for institutional business intelligence. Design/methodology/approach: The design of a data warehouse…

Using Students' Performance to Improve Ontologies for Intelligent E-Learning System

ERIC Educational Resources Information Center

Icoz, Kutay; Sanalan, Vehbi A.; Ozdemir, Esra Benli; Kaya, Sukru; Cakar, Mehmet Akif

2015-01-01

Ontologies have often been recommended for E-learning systems, but few efforts have successfully incorporated student data to represent knowledge conceptualizations. Defining key concepts and their relations between each other establishes the backbone of our E-learning system. The system guides an individual student through his/her course by…

Learning How to Construct Models of Dynamic Systems: An Initial Evaluation of the Dragoon Intelligent Tutoring System

ERIC Educational Resources Information Center

VanLehn, Kurt; Wetzel, Jon; Grover, Sachin; van de Sande, Brett

2017-01-01

Constructing models of dynamic systems is an important skill in both mathematics and science instruction. However, it has proved difficult to teach. Dragoon is an intelligent tutoring system intended to quickly and effectively teach this important skill. This paper describes Dragoon and an evaluation of it. The evaluation randomly assigned…

Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1989-01-01

Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

Production system chunking in SOAR: Case studies in automated learning

NASA Technical Reports Server (NTRS)

Allen, Robert

1989-01-01

A preliminary study of SOAR, a general intelligent architecture for automated problem solving and learning, is presented. The underlying principles of universal subgoaling and chunking were applied to a simple, yet representative, problem in artificial intelligence. A number of problem space representations were examined and compared. It is concluded that learning is an inherent and beneficial aspect of problem solving. Additional studies are suggested in domains relevant to mission planning and to SOAR itself.

Artificial Intelligence: The Expert Way.

ERIC Educational Resources Information Center

Bitter, Gary G.

1989-01-01

Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

A Hypermedia Approach to the Design of an Intelligent Tutoring System

DTIC Science & Technology

1991-09-01

23 3. Artist and Exploration Method ........................................... 24 4. Research method...LIMITATIONS AND FUTURE RESEARCH ............................................................... 76 v B. A CASE FOR HYPERMEDIA LEARNING ENVIRONMENTS...119 vi I. INTRODUCTION Most of the prior research in the field of intelligent tutoring systems (ITS) has focused on

The Design and Development of the Dragoon Intelligent Tutoring System for Model Construction: Lessons Learned

ERIC Educational Resources Information Center

Wetzel, Jon; VanLehn, Kurt; Butler, Dillan; Chaudhari, Pradeep; Desai, Avaneesh; Feng, Jingxian; Grover, Sachin; Joiner, Reid; Kong-Sivert, Mackenzie; Patade, Vallabh; Samala, Ritesh; Tiwari, Megha; van de Sande, Brett

2017-01-01

This paper describes Dragoon, a simple intelligent tutoring system which teaches the construction of models of dynamic systems. Modelling is one of seven practices dictated in two new sets of educational standards in the U.S.A., and Dragoon is one of the first systems for teaching model construction for dynamic systems. Dragoon can be classified…

Evolution of an Intelligent Deductive Logic Tutor Using Data-Driven Elements

ERIC Educational Resources Information Center

Mostafavi, Behrooz; Barnes, Tiffany

2017-01-01

Deductive logic is essential to a complete understanding of computer science concepts, and is thus fundamental to computer science education. Intelligent tutoring systems with individualized instruction have been shown to increase learning gains. We seek to improve the way deductive logic is taught in computer science by developing an intelligent,…

An Interview Reflection on "Intelligent Tutoring Goes to School in the Big City"

ERIC Educational Resources Information Center

Koedinger, Kenneth R.; Aleven, Vincent

2016-01-01

Our 1997 article in "IJAIED" reported on a study that showed that a new algebra curriculum with an embedded intelligent tutoring system (the Algebra Cognitive Tutor) dramatically enhanced high-school students' learning. The main motivation for the study was to demonstrate that intelligent tutors that have cognitive science research…

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

NASA Astrophysics Data System (ADS)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

[Remote intelligent Brunnstrom assessment system for upper limb rehabilitation for post-stroke based on extreme learning machine].

PubMed

Wang, Yue; Yu, Lei; Fu, Jianming; Fang, Qiang

2014-04-01

In order to realize an individualized and specialized rehabilitation assessment of remoteness and intelligence, we set up a remote intelligent assessment system of upper limb movement function of post-stroke patients during rehabilitation. By using the remote rehabilitation training sensors and client data sampling software, we collected and uploaded the gesture data from a patient's forearm and upper arm during rehabilitation training to database of the server. Then a remote intelligent assessment system, which had been developed based on the extreme learning machine (ELM) algorithm and Brunnstrom stage assessment standard, was used to evaluate the gesture data. To evaluate the reliability of the proposed method, a group of 23 stroke patients, whose upper limb movement functions were in different recovery stages, and 4 healthy people, whose upper limb movement functions were normal, were recruited to finish the same training task. The results showed that, compared to that of the experienced rehabilitation expert who used the Brunnstrom stage standard table, the accuracy of the proposed remote Brunnstrom intelligent assessment system can reach a higher level, as 92.1%. The practical effects of surgery have proved that the proposed system could realize the intelligent assessment of upper limb movement function of post-stroke patients remotely, and it could also make the rehabilitation of the post-stroke patients at home or in a community care center possible.

ICCE/ICCAI 2000 Full & Short Papers (Intelligent Tutoring Systems).

ERIC Educational Resources Information Center

2000

This document contains the full and short papers on intelligent tutoring systems (ITS) from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a framework for Internet-based distributed learning; a fuzzy-based assessment for the Perl tutoring…

Evaluation Methods for Intelligent Tutoring Systems Revisited

ERIC Educational Resources Information Center

Greer, Jim; Mark, Mary

2016-01-01

The 1993 paper in "IJAIED" on evaluation methods for Intelligent Tutoring Systems (ITS) still holds up well today. Basic evaluation techniques described in that paper remain in use. Approaches such as kappa scores, simulated learners and learning curves are refinements on past evaluation techniques. New approaches have also arisen, in…

Intelligent Tutoring Systems and Learning Outcomes: A Meta-Analysis

ERIC Educational Resources Information Center

Ma, Wenting; Adesope, Olusola O.; Nesbit, John C.; Liu, Qing

2014-01-01

Intelligent Tutoring Systems (ITS) are computer programs that model learners' psychological states to provide individualized instruction. They have been developed for diverse subject areas (e.g., algebra, medicine, law, reading) to help learners acquire domain-specific, cognitive and metacognitive knowledge. A meta-analysis was conducted on…

Towards a Collaborative Intelligent Tutoring System Classification Scheme

ERIC Educational Resources Information Center

Harsley, Rachel

2014-01-01

This paper presents a novel classification scheme for Collaborative Intelligent Tutoring Systems (CITS), an emergent research field. The three emergent classifications of CITS are unstructured, semi-structured, and fully structured. While all three types of CITS offer opportunities to improve student learning gains, the full extent to which these…

Deductive Error Diagnosis and Inductive Error Generalization for Intelligent Tutoring Systems.

ERIC Educational Resources Information Center

Hoppe, H. Ulrich

1994-01-01

Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

An Educational System for Learning Search Algorithms and Automatically Assessing Student Performance

ERIC Educational Resources Information Center

Grivokostopoulou, Foteini; Perikos, Isidoros; Hatzilygeroudis, Ioannis

2017-01-01

In this paper, first we present an educational system that assists students in learning and tutors in teaching search algorithms, an artificial intelligence topic. Learning is achieved through a wide range of learning activities. Algorithm visualizations demonstrate the operational functionality of algorithms according to the principles of active…

Introduction to Fuzzy Set Theory

NASA Technical Reports Server (NTRS)

Kosko, Bart

1990-01-01

An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

University Research Initiative Research Program Summaries

DTIC Science & Technology

1987-06-01

application to intelligent tutoring systems (John Anderson), o Autonomous learning systems (Jaime Carbonell), o Learning algorithms for parallel processing...test them. The primary project will be: o Learning mechanisms in scientific discovery (Herbert Simon). Tutoring systems. These projects are aimed at...near-term results. They 19 will produce tutors for training specific subject matter areas. These projects will push theories of learning forward by

Adaptive Fuzzy Systems in Computational Intelligence

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

New frontiers for intelligent content-based retrieval

NASA Astrophysics Data System (ADS)

Benitez, Ana B.; Smith, John R.

2001-01-01

In this paper, we examine emerging frontiers in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the capabilities of the systems to build and maintain situational or world models, utilize dynamic knowledge representation, exploit context, and leverage advanced reasoning and learning capabilities. We argue that these elements are essential to producing effective systems for retrieving audio-visual content at semantic levels matching those of human perception and cognition. In this paper, we review relevant research on the understanding of human intelligence and construction of intelligent system in the fields of cognitive psychology, artificial intelligence, semiotics, and computer vision. We also discus how some of the principal ideas form these fields lead to new opportunities and capabilities for content-based retrieval systems. Finally, we describe some of our efforts in these directions. In particular, we present MediaNet, a multimedia knowledge presentation framework, and some MPEG-7 description tools that facilitate and enable intelligent content-based retrieval.

New frontiers for intelligent content-based retrieval

NASA Astrophysics Data System (ADS)

Benitez, Ana B.; Smith, John R.

2000-12-01

In this paper, we examine emerging frontiers in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the capabilities of the systems to build and maintain situational or world models, utilize dynamic knowledge representation, exploit context, and leverage advanced reasoning and learning capabilities. We argue that these elements are essential to producing effective systems for retrieving audio-visual content at semantic levels matching those of human perception and cognition. In this paper, we review relevant research on the understanding of human intelligence and construction of intelligent system in the fields of cognitive psychology, artificial intelligence, semiotics, and computer vision. We also discus how some of the principal ideas form these fields lead to new opportunities and capabilities for content-based retrieval systems. Finally, we describe some of our efforts in these directions. In particular, we present MediaNet, a multimedia knowledge presentation framework, and some MPEG-7 description tools that facilitate and enable intelligent content-based retrieval.

Social Intelligence in a Human-Machine Collaboration System

NASA Astrophysics Data System (ADS)

Nakajima, Hiroshi; Morishima, Yasunori; Yamada, Ryota; Brave, Scott; Maldonado, Heidy; Nass, Clifford; Kawaji, Shigeyasu

In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

The New Challenges for E-learning: The Educational Semantic Web

ERIC Educational Resources Information Center

Aroyo, Lora; Dicheva, Darina

2004-01-01

The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it?…

Multidimensional Learner Model In Intelligent Learning System

NASA Astrophysics Data System (ADS)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks

NASA Astrophysics Data System (ADS)

Sadek, Add; Basha, Nagi

Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.

Building intelligent systems: Artificial intelligence research at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Friedland, P.; Lum, H.

1987-01-01

The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a truly autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.

Building intelligent systems - Artificial intelligence research at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Friedland, Peter; Lum, Henry

1987-01-01

The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a 'truly' autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.

Coupling between Metacognition and Emotions during STEM Learning with Advanced Learning Technologies: A Critical Analysis, Implications for Future Research, and Design of Learning Systems

ERIC Educational Resources Information Center

Azevedo, Roger; Mudrick, Nicholas; Taub, Michelle; Wortha, Franz

2017-01-01

Metacognition and emotions play a critical role in learners' ability to monitor and regulate their learning about 21st-century skills related to science, technology, engineering, and mathematics (STEM) content while using advanced learning technologies (ALTs; e.g., intelligent tutoring systems, serious games, hypermedia, augmented reality). In…

An Ontology for Learning Services on the Shop Floor

ERIC Educational Resources Information Center

Ullrich, Carsten

2016-01-01

An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

Adaptive versus Learner Control in a Multiple Intelligence Learning Environment

ERIC Educational Resources Information Center

Kelly, Declan

2008-01-01

Within the field of technology enhanced learning, adaptive educational systems offer an advanced form of learning environment that attempts to meet the needs of different students. Such systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, using the…

Adapting Collaboration Dialogue in Response to Intelligent Tutoring System Feedback

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

2015-01-01

To be able to provide better support for collaborative learning in Intelligent Tutoring Systems, it is important to understand how collaboration patterns change. Prior work has looked at the interdependencies between utterances and the change of dialogue over time, but it has not addressed how dialogue changes during a lesson, an analysis that…

Working with Pedagogical Agents: Understanding the "Back End" of an Intelligent Tutoring System

ERIC Educational Resources Information Center

Wolfe, Christopher; Widmer, Colin L.; Weil, Audrey M.; Cedillos-Whynott, Elizabeth M.

2015-01-01

Students in an undergraduate psychology course on Learning and Cognition used SKO (formerly AutoTutor Lite), an Intelligent Tutoring System, to create interactive lessons in which a pedagogic agent (animated avatar) engages users in a tutorial dialogue. After briefly describing the technology and underlying psychological theory, data from an…

Predicting Correctness of Problem Solving from Low-Level Log Data in Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey

2009-01-01

This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…

Designing Distributed Learning Environments with Intelligent Software Agents

ERIC Educational Resources Information Center

Lin, Fuhua, Ed.

2005-01-01

"Designing Distributed Learning Environments with Intelligent Software Agents" reports on the most recent advances in agent technologies for distributed learning. Chapters are devoted to the various aspects of intelligent software agents in distributed learning, including the methodological and technical issues on where and how intelligent agents…

Experimentation of cooperative learning model Numbered Heads Together (NHT) type by concept maps and Teams Games Tournament (TGT) by concept maps in terms of students logical mathematics intellegences

NASA Astrophysics Data System (ADS)

Irawan, Adi; Mardiyana; Retno Sari Saputro, Dewi

2017-06-01

This research is aimed to find out the effect of learning model towards learning achievement in terms of students’ logical mathematics intelligences. The learning models that were compared were NHT by Concept Maps, TGT by Concept Maps, and Direct Learning model. This research was pseudo experimental by factorial design 3×3. The population of this research was all of the students of class XI Natural Sciences of Senior High School in all regency of Karanganyar in academic year 2016/2017. The conclusions of this research were: 1) the students’ achievements with NHT learning model by Concept Maps were better than students’ achievements with TGT model by Concept Maps and Direct Learning model. The students’ achievements with TGT model by Concept Maps were better than the students’ achievements with Direct Learning model. 2) The students’ achievements that exposed high logical mathematics intelligences were better than students’ medium and low logical mathematics intelligences. The students’ achievements that exposed medium logical mathematics intelligences were better than the students’ low logical mathematics intelligences. 3) Each of student logical mathematics intelligences with NHT learning model by Concept Maps has better achievement than students with TGT learning model by Concept Maps, students with NHT learning model by Concept Maps have better achievement than students with the direct learning model, and the students with TGT by Concept Maps learning model have better achievement than students with Direct Learning model. 4) Each of learning model, students who have logical mathematics intelligences have better achievement then students who have medium logical mathematics intelligences, and students who have medium logical mathematics intelligences have better achievement than students who have low logical mathematics intelligences.

Intelligent transportation systems for work zones : deployment benefits and lessons learned

DOT National Transportation Integrated Search

2000-12-01

This paper presents what has been learned in four principal areas of arterial management: 1) adaptive control strategies; 2) advanced traveler information systems; 3) automated enforcement; and 4) integration. The levels of deployment, benefits, depl...

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A mathematical model of the creative control process is presented that illustrates the use for mobile robots. Examples from a variety of intelligent mobile robot applications are also presented. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots that could lead to many applications.

A User-Centric Adaptive Learning System for E-Learning 2.0

ERIC Educational Resources Information Center

Huang, Shiu-Li; Shiu, Jung-Hung

2012-01-01

The success of Web 2.0 inspires e-learning to evolve into e-learning 2.0, which exploits collective intelligence to achieve user-centric learning. However, searching for suitable learning paths and content for achieving a learning goal is time consuming and troublesome on e-learning 2.0 platforms. Therefore, introducing formal learning in these…

Does it really matter whether students' contributions are spoken versus typed in an intelligent tutoring system with natural language?

PubMed

D'Mello, Sidney K; Dowell, Nia; Graesser, Arthur

2011-03-01

There is the question of whether learning differs when students speak versus type their responses when interacting with intelligent tutoring systems with natural language dialogues. Theoretical bases exist for three contrasting hypotheses. The speech facilitation hypothesis predicts that spoken input will increase learning, whereas the text facilitation hypothesis predicts typed input will be superior. The modality equivalence hypothesis claims that learning gains will be equivalent. Previous experiments that tested these hypotheses were confounded by automated speech recognition systems with substantial error rates that were detected by learners. We addressed this concern in two experiments via a Wizard of Oz procedure, where a human intercepted the learner's speech and transcribed the utterances before submitting them to the tutor. The overall pattern of the results supported the following conclusions: (1) learning gains associated with spoken and typed input were on par and quantitatively higher than a no-intervention control, (2) participants' evaluations of the session were not influenced by modality, and (3) there were no modality effects associated with differences in prior knowledge and typing proficiency. Although the results generally support the modality equivalence hypothesis, highly motivated learners reported lower cognitive load and demonstrated increased learning when typing compared with speaking. We discuss the implications of our findings for intelligent tutoring systems that can support typed and spoken input.

An Artificial Intelligence Approach to Analyzing Student Errors in Statistics.

ERIC Educational Resources Information Center

Sebrechts, Marc M.; Schooler, Lael J.

1987-01-01

Describes the development of an artificial intelligence system called GIDE that analyzes student errors in statistics problems by inferring the students' intentions. Learning strategies involved in problem solving are discussed and the inclusion of goal structures is explained. (LRW)

Novel associative-memory-based self-learning neurocontrol model

NASA Astrophysics Data System (ADS)

Chen, Ke

1992-09-01

Intelligent control is an important field of AI application, which is closely related to machine learning, and the neurocontrol is a kind of intelligent control that controls actions of a physical system or a plant. Linear associative memory model is a good analytic tool for artificial neural networks. In this paper, we present a novel self-learning neurocontrol on the basis of the linear associative memory model to support intelligent control. Using our self-learning neurocontrol model, the learning process is viewed as an extension of one of J. Piaget's developmental stages. After a particular linear associative model developed by us is presented, a brief introduction to J. Piaget's cognitive theory is described as the basis of our self-learning style control. It follows that the neurocontrol model is presented, which usually includes two learning stages, viz. primary learning and high-level learning. As a demonstration of our neurocontrol model, an example is also presented with simulation techniques, called that `bird' catches an aim. The tentative experimental results show that the learning and controlling performance of this approach is surprisingly good. In conclusion, future research is pointed out to improve our self-learning neurocontrol model and explore other areas of application.

Intelligent tutoring system for clinical reasoning skill acquisition in dental students.

PubMed

Suebnukarn, Siriwan

2009-10-01

Learning clinical reasoning is an important core activity of the modern dental curriculum. This article describes an intelligent tutoring system (ITS) for clinical reasoning skill acquisition. The system is designed to provide an experience that emulates that of live human-tutored problem-based learning (PBL) sessions as much as possible, while at the same time permitting the students to participate collaboratively from disparate locations. The system uses Bayesian networks to model individual student knowledge and activity, as well as that of the group. Tutoring algorithms use the models to generate tutoring hints. The system incorporates a multimodal interface that integrates text and graphics so as to provide a rich communication channel between the students and the system, as well as among students in the group. Comparison of learning outcomes shows that student clinical reasoning gains from the ITS are similar to those obtained from human-tutored sessions.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers

ERIC Educational Resources Information Center

Gracious, F. L. Antony; Shyla, F. L. Jasmine Anne

2012-01-01

The present study Multiple Intelligence and Digital Learning Awareness of prospective B.Ed teachers was probed to find the relationship between Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers. Data for the study were collected using self made Multiple Intelligence Inventory and Digital Learning Awareness Scale.…

A Distributed Intelligent E-Learning System

ERIC Educational Resources Information Center

Kristensen, Terje

2016-01-01

An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…

Affect Recognition through Facebook for Effective Group Profiling towards Personalized Instruction

ERIC Educational Resources Information Center

Troussas, Christos; Espinosa, Kurt Junshean; Virvou, Maria

2016-01-01

Social networks are progressively being considered as an intense thought for learning. Particularly in the research area of Intelligent Tutoring Systems, they can create intuitive, versatile and customized e-learning systems which can advance the learning process by revealing the capacities and shortcomings of every learner and by customizing the…

An Autonomous Learning System of Bengali Characters Using Web-Based Intelligent Handwriting Recognition

ERIC Educational Resources Information Center

Khatun, Nazma; Miwa, Jouji

2016-01-01

This research project was aimed to develop an intelligent Bengali handwriting education system to improve the literacy level in Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. Here, we developed a prototype of web-based (iPhone/smartphone or computer browser) intelligent…

Analysing Student Programs in the PHP Intelligent Tutoring System

ERIC Educational Resources Information Center

Weragama, Dinesha; Reye, Jim

2014-01-01

Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…

Cooperative learning model with high order thinking skills questions: an understanding on geometry

NASA Astrophysics Data System (ADS)

Sari, P. P.; Budiyono; Slamet, I.

2018-05-01

Geometry, a branch of mathematics, has an important role in mathematics learning. This research aims to find out the effect of learning model, emotional intelligence, and the interaction between learning model and emotional intelligence toward students’ mathematics achievement. This research is quasi-experimental research with 2 × 3 factorial design. The sample in this research included 179 Senior High School students on 11th grade in Sukoharjo Regency, Central Java, Indonesia in academic year of 2016/2017. The sample was taken by using stratified cluster random sampling. The results showed that: the student are taught by Thinking Aloud Pairs Problem-Solving using HOTs questions provides better mathematics learning achievement than Make A Match using HOTs questions. High emotional intelligence students have better mathematics learning achievement than moderate and low emotional intelligence students, and moderate emotional intelligence students have better mathematics learning achievement than low emotional intelligence students. There is an interaction between learning model and emotional intelligence, and these affect mathematics learning achievement. We conclude that appropriate learning model can support learning activities become more meaningful and facilitate students to understand material. For further research, we suggest to explore the contribution of other aspects in cooperative learning modification to mathematics achievement.

Lessons Learned and Flight Results from the F15 Intelligent Flight Control System Project

NASA Technical Reports Server (NTRS)

Bosworth, John

2006-01-01

A viewgraph presentation on the lessons learned and flight results from the F15 Intelligent Flight Control System (IFCS) project is shown. The topics include: 1) F-15 IFCS Project Goals; 2) Motivation; 3) IFCS Approach; 4) NASA F-15 #837 Aircraft Description; 5) Flight Envelope; 6) Limited Authority System; 7) NN Floating Limiter; 8) Flight Experiment; 9) Adaptation Goals; 10) Handling Qualities Performance Metric; 11) Project Phases; 12) Indirect Adaptive Control Architecture; 13) Indirect Adaptive Experience and Lessons Learned; 14) Gen II Direct Adaptive Control Architecture; 15) Current Status; 16) Effect of Canard Multiplier; 17) Simulated Canard Failure Stab Open Loop; 18) Canard Multiplier Effect Closed Loop Freq. Resp.; 19) Simulated Canard Failure Stab Open Loop with Adaptation; 20) Canard Multiplier Effect Closed Loop with Adaptation; 21) Gen 2 NN Wts from Simulation; 22) Direct Adaptive Experience and Lessons Learned; and 23) Conclusions

Socioscape: Real-Time Analysis of Dynamic Heterogeneous Networks In Complex Socio-Cultural Systems

DTIC Science & Technology

2015-10-22

Cluster Mixed-Membership Blockmodel for Time-Evolving Networks, Proceedings of the 14th International Conference on Artifical Intelligence and...Learning With Simultaneous Orthogonal Matching Pursuit, Proceedings of the 13th International Conference on Artifical Intelligence and Statistics

Intelligent E-Learning Systems: Automatic Construction of Ontologies

NASA Astrophysics Data System (ADS)

Peso, Jesús del; de Arriaga, Fernando

2008-05-01

During the last years a new generation of Intelligent E-Learning Systems (ILS) has emerged with enhanced functionality due, mainly, to influences from Distributed Artificial Intelligence, to the use of cognitive modelling, to the extensive use of the Internet, and to new educational ideas such as the student-centered education and Knowledge Management. The automatic construction of ontologies provides means of automatically updating the knowledge bases of their respective ILS, and of increasing their interoperability and communication among them, sharing the same ontology. The paper presents a new approach, able to produce ontologies from a small number of documents such as those obtained from the Internet, without the assistance of large corpora, by using simple syntactic rules and some semantic information. The method is independent of the natural language used. The use of a multi-agent system increases the flexibility and capability of the method. Although the method can be easily improved, the results so far obtained, are promising.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Pavlovian, Skinner, and Other Behaviourists' Contributions to AI. Chapter 9

NASA Technical Reports Server (NTRS)

Kosinski, Withold; Zaczek-Chrzanowska, Dominika

2007-01-01

A version of the definition of intelligent behaviour will be supplied in the context of real and artificial systems. Short presentation of principles of learning, starting with Pavlovian s classical conditioning through reinforced response and operant conditioning of Thorndike and Skinner and finishing with cognitive learning of Tolman and Bandura will be given. The most important figures within behaviourism, especially those with contribution to AI, will be described. Some tools of artificial intelligence that act according to those principles will be presented. An attempt will be made to show when some simple rules for behaviour modifications can lead to a complex intelligent behaviour.

Using Computers Intelligently in Tertiary Education. A Collection of Papers Presented to the Australian Society for Computers in Learning (Sydney, New South Wales, Australia, November 29-December 3, 1987).

ERIC Educational Resources Information Center

Barrett, John, Ed.; Hedberg, John, Ed.

The 63 papers in this collection include two keynote addresses: "Patient Simulation Using Interactive Video: An Application" (Joseph V. Henderson), and "Intelligent Tutoring Systems: Practice Opportunities and Explanatory Models" (Alan Lesgold). The remaining papers are grouped under five topics: (1) Artificial Intelligence,…

Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

NASA Astrophysics Data System (ADS)

Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

2013-03-01

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

NASA Astrophysics Data System (ADS)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

Experiential effects on mirror systems and social learning: implications for social intelligence.

PubMed

Reader, Simon M

2014-04-01

Investigations of biases and experiential effects on social learning, social information use, and mirror systems can usefully inform one another. Unconstrained learning is predicted to shape mirror systems when the optimal response to an observed act varies, but constraints may emerge when immediate error-free responses are required and evolutionary or developmental history reliably predicts the optimal response. Given the power of associative learning, such constraints may be rare.

Artificial Intelligence and CALL.

ERIC Educational Resources Information Center

Underwood, John H.

The potential application of artificial intelligence (AI) to computer-assisted language learning (CALL) is explored. Two areas of AI that hold particular interest to those who deal with language meaning--knowledge representation and expert systems, and natural-language processing--are described and examples of each are presented. AI contribution…

A Starter's Guide to Artificial Intelligence.

ERIC Educational Resources Information Center

McConnell, Barry A.; McConnell, Nancy J.

1988-01-01

Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

NASA Technical Reports Server (NTRS)

Lin, Paul P.; Jules, Kenol

2002-01-01

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.

A machine learning system to improve heart failure patient assistance.

PubMed

Guidi, Gabriele; Pettenati, Maria Chiara; Melillo, Paolo; Iadanza, Ernesto

2014-11-01

In this paper, we present a clinical decision support system (CDSS) for the analysis of heart failure (HF) patients, providing various outputs such as an HF severity evaluation, HF-type prediction, as well as a management interface that compares the different patients' follow-ups. The whole system is composed of a part of intelligent core and of an HF special-purpose management tool also providing the function to act as interface for the artificial intelligence training and use. To implement the smart intelligent functions, we adopted a machine learning approach. In this paper, we compare the performance of a neural network (NN), a support vector machine, a system with fuzzy rules genetically produced, and a classification and regression tree and its direct evolution, which is the random forest, in analyzing our database. Best performances in both HF severity evaluation and HF-type prediction functions are obtained by using the random forest algorithm. The management tool allows the cardiologist to populate a "supervised database" suitable for machine learning during his or her regular outpatient consultations. The idea comes from the fact that in literature there are a few databases of this type, and they are not scalable to our case.

Learning material recommendation based on case-based reasoning similarity scores

NASA Astrophysics Data System (ADS)

Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

Evaluating the relation between memory and intelligence in children with learning disabilities.

PubMed

Hoerig, Dianne C; David, Andrew S; D'Amato, Rik Carl

2002-12-01

Although both intelligence tests and memory tests are commonly used in neuropsychological examinations, the relationship between memory and intelligence has not been fully explored, particularly for children having learning disabilities. Memory, or the ability to retain information, was evaluated using the Test of Memory and Learning, a recently released test that gives a comprehensive measure of global memory functioning. This, and the Wechsler Intelligence Scale for Children-Third Edition, used to assess intelligence, were given to 80 students with learning disabilities. The correlation between a global measure of memory and a global measure f intelligence was significant (r = .59), indicating that memory should be viewed as an important component when evaluating children with learning disabilities.

Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2012-01-01

The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri vocational school students

NASA Astrophysics Data System (ADS)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-05-01

This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri Vocational School students

NASA Astrophysics Data System (ADS)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-03-01

This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

Cognitive Task Analysis and Intelligent Computer-Based Training Systems: Lessons Learned from Coached Practice Environments in Air Force Avionics.

ERIC Educational Resources Information Center

Katz, Sandra N.; Hall, Ellen; Lesgold, Alan

This paper describes some results of a collaborative effort between the University of Pittsburgh and the Air Force to develop advanced troubleshooting training for F-15 maintenance technicians. The focus is on the cognitive task methodology used in the development of three intelligent tutoring systems to inform their instructional content and…

A Study of the Design and Implementation of the ASR-Based iCASL System with Corrective Feedback to Facilitate English Learning

ERIC Educational Resources Information Center

Wang, Yi-Hsuan; Young, Shelley Shwu-Ching

2014-01-01

The purpose of the study is to explore and describe how to implement a pedagogical ASR-based intelligent computer-assisted speaking learning (iCASL) system to support adult learners with a private, flexible and individual learning environment to practice English pronunciation. The iCASL system integrates multiple levels of corrective feedback and…

Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

ERIC Educational Resources Information Center

Lajoie, Susanne P.; Azevedo, Roger; Fleiszer, David M.

1998-01-01

Describes the development of a simulation-based intelligent tutoring system for nurses working in a surgical intensive care unit. Highlights include situative learning theories and models of instruction, modeling expertise, complex decision making, linking theories of learning to the design of computer-based learning environments, cognitive task…

Conceptual Learning with Multiple Graphical Representations: Intelligent Tutoring Systems Support for Sense-Making and Fluency-Building Processes

ERIC Educational Resources Information Center

Rau, Martina A.

2013-01-01

Most learning environments in the STEM disciplines use multiple graphical representations along with textual descriptions and symbolic representations. Multiple graphical representations are powerful learning tools because they can emphasize complementary aspects of complex learning contents. However, to benefit from multiple graphical…

The Effect Of The Materials Based On Multiple Intelligence Theory Upon The Intelligence Groups' Learning Process

NASA Astrophysics Data System (ADS)

Oral, I.; Dogan, O.

2007-04-01

The aim of this study is to find out the effect of the course materials based on Multiple Intelligence Theory upon the intelligence groups' learning process. In conclusion, the results proved that the materials prepared according to Multiple Intelligence Theory have a considerable effect on the students' learning process. This effect was particularly seen on the student groups of the musical-rhythmic, verbal-linguistic, interpersonal-social and naturalist intelligence.

Artificial Intelligence and NASA Data Used to Discover Eighth Planet Circling Distant Star

NASA Image and Video Library

2017-12-12

Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light years from Earth. The planet was discovered in data from NASA’s Kepler space telescope. The newly-discovered Kepler-90i -- a sizzling hot, rocky planet that orbits its star once every 14.4 days -- was found by researchers from Google and The University of Texas at Austin using machine learning. Machine learning is an approach to artificial intelligence in which computers “learn.” In this case, computers learned to identify planets by finding in Kepler data instances where the telescope recorded signals from planets beyond our solar system, known as exoplanets. Video Credit: NASA Ames Research Center / Google

Proceedings of the 1986 IEEE international conference on systems, man and cybernetics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1986-01-01

This book presents the papers given at a conference on man-machine systems. Topics considered at the conference included neural model-based cognitive theory and engineering, user interfaces, adaptive and learning systems, human interaction with robotics, decision making, the testing and evaluation of expert systems, software development, international conflict resolution, intelligent interfaces, automation in man-machine system design aiding, knowledge acquisition in expert systems, advanced architectures for artificial intelligence, pattern recognition, knowledge bases, and machine vision.

A Large-Scale Evaluation of an Intelligent Discovery World: Smithtown.

ERIC Educational Resources Information Center

Shute, Valerie J.; Glaser, Robert

1990-01-01

Presents an evaluation of "Smithtown," an intelligent tutoring system designed to teach inductive inquiry skills and principles of basic microeconomics. Two studies of individual differences in learning are described, including a comparison of knowledge acquisition with traditional instruction; hypotheses tested are discussed; and the…

Soar: A Unified Theory of Cognition?

ERIC Educational Resources Information Center

Waldrop, M. Mitchell

1988-01-01

Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

A Multidisciplinary Model for Development of Intelligent Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Park, Ok-choon; Seidel, Robert J.

1989-01-01

Proposes a schematic multidisciplinary model to help developers of intelligent computer-assisted instruction (ICAI) identify the types of required expertise and integrate them into a system. Highlights include domain types and expertise; knowledge acquisition; task analysis; knowledge representation; student modeling; diagnosis of learning needs;…

Case study and lessons learned for the Great Lakes ITS Program, Airport ITS Integration and the Road Infrastructure Management System projects, final report, Wayne County, Michigan

DOT National Transportation Integrated Search

2007-03-02

This report presents the case study and lessons learned for the national evaluation of the Great Lakes Intelligent Transportation Systems (GLITS) Airport ITS Integration and Road Infrastructure Management System (RIMS) projects. The Airport ITS Integ...

Collaborative Learning and Knowledge-Construction through a Knowledge-Based WWW Authoring Tool.

ERIC Educational Resources Information Center

Haugsjaa, Erik

This paper outlines hurdles to using the World Wide Web for learning, specifically in a collaborative knowledge-construction environment. Theoretical solutions based directly on existing Web environments, as well as on research and system prototypes in the areas of Intelligent Tutoring Systems (ITS) and ITS authoring systems, are suggested. Topics…

Adaptivity in Educational Systems for Language Learning: A Review

ERIC Educational Resources Information Center

Slavuj, Vanja; Meštrovic, Ana; Kovacic, Božidar

2017-01-01

Adaptive and intelligent instructional systems are used to deal with the issue of learning personalisation in contexts where human instructors are not immediately available, so their role is transferred entirely or in part onto the computer. Even though such systems are mostly developed for well-defined domains that have a rather straightforward…

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

PubMed Central

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-01-01

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced. PMID:26690164

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

PubMed

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-12-04

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

NASA Technical Reports Server (NTRS)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

What have we learned about intelligent transportation systems? Chapter 9, What have we learned about ITS? Final comments

DOT National Transportation Integrated Search

2005-09-30

This document presents the findings of the national evaluation of the 511 telephone traveler information system Model Deployment in Arizona. The United States Department of Transportation (U.S. DOT) National 511 Model Deployment supported a wid...

Representing Learning With Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence, for instance, in diagnosis and expert systems, as a unified qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several fields including artificial intelligence, decision theory and statistics, and provides an important bridge between these communities. This paper shows by way of example that these models can be extended to machine learning, neural networks and knowledge discovery by representing the notion of a sample on the graphical model. Not only does this allow a flexible variety of learning problems to be represented, it also provides the means for representing the goal of learning and opens the way for the automatic development of learning algorithms from specifications.

Blindness in designing intelligent systems

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1988-01-01

New investigations of the foundations of artificial intelligence are challenging the hypothesis that problem solving is the cornerstone of intelligence. New distinctions among three domains of concern for humans--description, action, and commitment--have revealed that the design process for programmable machines, such as expert systems, is based on descriptions of actions and induces blindness to nonanalytic action and commitment. Design processes focusing in the domain of description are likely to yield programs like burearcracies: rigid, obtuse, impersonal, and unable to adapt to changing circumstances. Systems that learn from their past actions, and systems that organize information for interpretation by human experts, are more likely to be successful in areas where expert systems have failed.

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

NASA Astrophysics Data System (ADS)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

Intelligent Computer-Assisted Language Learning.

ERIC Educational Resources Information Center

Harrington, Michael

1996-01-01

Introduces the field of intelligent computer assisted language learning (ICALL) and relates them to current practice in computer assisted language learning (CALL) and second language learning. Points out that ICALL applies expertise from artificial intelligence and the computer and cognitive sciences to the development of language learning…

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Individualized Special Education with Cognitive Skill Assessment.

ERIC Educational Resources Information Center

Kurhila, Jaakko; Laine, Tei

2000-01-01

Describes AHMED (Adaptive and Assistive Hypermedia in Education), a computer learning environment which supports the evaluation of disabled children's cognitive skills in addition to supporting openness in learning materials and adaptivity in learning events. Discusses cognitive modeling and compares it to previous intelligent tutoring systems.…

Using S-P Chart and Bloom Taxonomy to Develop Intelligent Formative Assessment Tool

ERIC Educational Resources Information Center

Chang, Wen-Chih; Yang, Hsuan-Che; Shih, Timothy K.; Chao, Louis R.

2009-01-01

E-learning provides a convenient and efficient way for learning. Formative assessment not only guides student in instruction and learning, diagnose skill or knowledge gaps, but also measures progress and evaluation. An efficient and convenient e-learning formative assessment system is the key character for e-learning. However, most e-learning…

A Learning Framework for Knowledge Building and Collective Wisdom Advancement in Virtual Learning Communities

ERIC Educational Resources Information Center

Gan, Yongcheng; Zhu, Zhiting

2007-01-01

This study represents an effort to construct a learning framework for knowledge building and collective wisdom advancement in a virtual learning community (VLC) from the perspectives of system wholeness, intelligence wholeness and dynamics, learning models, and knowledge management. It also tries to construct the zone of proximal development (ZPD)…

Essays on Learning through Practice

ERIC Educational Resources Information Center

Feng, Junchen

2017-01-01

The future of education is human expertise and artificial intelligence working in conjunction, a revolution that will change the education as we know it. The Intelligent Tutoring System is a key component of this future. A quantitative measurement of efficacies of practice to heterogeneous learners is the cornerstone of building an effective…

How Can Intelligent CAL Better Adapt to Learners?

ERIC Educational Resources Information Center

Boyd, Gary McI.; Mitchell, P. David

1992-01-01

Discusses intelligent computer-aided learning (ICAL) support systems and considers learner characteristics as elements of ICAL student models. Cybernetic theory and attribute-treatment results are discussed, six components of a student model for tutoring are described, and methods for determining the student's model of the tutor are examined. (22…

A New Approach of an Intelligent E-Learning System Based on Learners' Skill Level and Learners' Success Rate

ERIC Educational Resources Information Center

Mohamed, Hafidi; Lamia, Mahnane

2015-01-01

Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper,…

Implementation of a Model-Tracing-Based Learning Diagnosis System to Promote Elementary Students' Learning in Mathematics

ERIC Educational Resources Information Center

Chu, Yian-Shu; Yang, Haw-Ching; Tseng, Shian-Shyong; Yang, Che-Ching

2014-01-01

Of all teaching methods, one-to-one human tutoring is the most powerful method for promoting learning. To achieve this aim and reduce teaching load, researchers developed intelligent tutoring systems (ITSs) to employ one-to-one tutoring (Aleven, McLaren, & Sewall, 2009; Aleven, McLaren, Sewall, & Koedinger, 2009; Anderson, Corbett,…

Lecture Notes in Artificial Intelligence 689: Methodologies for Intelligent Systems: International Symposium, ISMIS 󈨡 (7th) Held at Trondheim (Norway) April 1993

DTIC Science & Technology

1993-06-18

expresses 171 From our earliest days we learn to perceive time as a result of two im- portant cognitive abilities : the awareness of change in the world...agent. - Learning and cognition are closely related. Between the levels of sensory percep- tion and abstract language there are several levels of...Kaufmann, Los Altos, California, 1988. Previously available as I Report PM-01-87, School of Mathematics , University of Bristol. [13] Y. Shoham

Defense Logistics Standard Systems Functional Requirements.

DTIC Science & Technology

1987-03-01

Artificial Intelligence - the development of a machine capability to perform functions normally concerned with human intelligence, such as learning , adapting...Basic Data Base Machine Configurations .... ......... D- 18 xx ~ ?f~~~vX PART I: MODELS - DEFENSE LOGISTICS STANDARD SYSTEMS FUNCTIONAL REQUIREMENTS...On-line, Interactive Access. Integrating user input and machine output in a dynamic, real-time, give-and- take process is considered the optimum mode

Intelligent Fuzzy Spelling Evaluator for e-Learning Systems

ERIC Educational Resources Information Center

Chakraborty, Udit Kr.; Konar, Debanjan; Roy, Samir; Choudhury, Sankhayan

2016-01-01

Evaluating Learners' Response in an e-Learning environment has been the topic of current research in areas of Human Computer Interaction, e-Learning, Education Technology and even Natural Language Processing. The current paper presents a twofold strategy to evaluate single word response of a learner in an e-Learning environment. The response of…

An Intelligent Mobile Location-Aware Book Recommendation System that Enhances Problem-Based Learning in Libraries

ERIC Educational Resources Information Center

Chen, Chih-Ming

2013-01-01

Despite rapid and continued adoption of mobile devices, few learning modes integrate with mobile technologies and libraries' environments as innovative learning modes that emphasize the key roles of libraries in facilitating learning. In addition, some education experts have claimed that transmitting knowledge to learners is not the only…

Emotional Intelligence and Self-Directed Learning Readiness among College Students Participating in a Leadership Development Program

ERIC Educational Resources Information Center

Radnitzer, Karl David

2010-01-01

The purpose of this study was to investigate possible relationships between self-directed learning readiness and emotional intelligence in a leadership development program and if self-directed learning leads to greater self-directed learning capabilities. Prior research has examined self-directed learning and emotional intelligence but never have…

What have we learned about intelligent transportation systems? Chapter 5, What have we learned about advanced public transportation systems?

DOT National Transportation Integrated Search

1995-12-01

THE PURPOSE OF THE STUDY REPORTED HERE WAS TO EXAMINE WHETHER AGE AND SPATIAL ABILITY ARE FACTORS THAT INFLUENCE A DRIVER'S ABILITY TO NAVIGATE AND TO USE NAVIGATIONAL DISPLAYS. THESE FACTORS WERE EXAMINED BECAUSE PREVIOUS RESEARCH SUGGESTS THAT SPAT...

Emerging CAE technologies and their role in Future Ambient Intelligence Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2011-03-01

Dramatic improvements are on the horizon in Computer Aided Engineering (CAE) and various simulation technologies. The improvements are due, in part, to the developments in a number of leading-edge technologies and their synergistic combinations/convergence. The technologies include ubiquitous, cloud, and petascale computing; ultra high-bandwidth networks, pervasive wireless communication; knowledge based engineering; networked immersive virtual environments and virtual worlds; novel human-computer interfaces; and powerful game engines and facilities. This paper describes the frontiers and emerging simulation technologies, and their role in the future virtual product creation and learning/training environments. The environments will be ambient intelligence environments, incorporating a synergistic combination of novel agent-supported visual simulations (with cognitive learning and understanding abilities); immersive 3D virtual world facilities; development chain management systems and facilities (incorporating a synergistic combination of intelligent engineering and management tools); nontraditional methods; intelligent, multimodal and human-like interfaces; and mobile wireless devices. The Virtual product creation environment will significantly enhance the productivity and will stimulate creativity and innovation in future global virtual collaborative enterprises. The facilities in the learning/training environment will provide timely, engaging, personalized/collaborative and tailored visual learning.

Applications of artificial intelligence to scientific research

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen

1986-01-01

Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

PubMed

Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

2012-10-22

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

PubMed Central

Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

2012-01-01

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

Implementation of Multiple Intelligences Supported Project-Based Learning in EFL/ESL Classrooms

ERIC Educational Resources Information Center

Bas, Gokhan

2008-01-01

This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…

An Investigation between Multiple Intelligences and Learning Styles

ERIC Educational Resources Information Center

Sener, Sabriye; Çokçaliskan, Ayten

2018-01-01

Exploring learning style and multiple intelligence type of learners can enable the students to identify their strengths and weaknesses and learn from them. It is also very important for teachers to understand their learners' learning styles and multiple intelligences since they can carefully identify their goals and design activities that can…

Expanding Learning and Social Interaction through Intelligent Systems Design: Implementing a Reputation and Recommender System for the Claremont Conversation Online

ERIC Educational Resources Information Center

Thoms, Brian

2009-01-01

In this dissertation I examine the design, construction and implementation of an online blog ratings and user recommender system for the Claremont Conversation Online (CCO). In line with constructivist learning models and practical information systems (IS) design, I implemented a blog ratings system (a system that can be extended to allow for…

Contributions Emotional Intelligence on Cognitive Learning Result of Biology of Senior High School Students in Medan, Indonesia

ERIC Educational Resources Information Center

Pratama, Anggi Tias; Corebima, Aloysius Duran

2016-01-01

Emotional intelligence is one of the factors affecting the success of students' learning results. Students having high emotional intelligence will be able to overcome the problems faced in school and in society. This research aims at investigating the correlation between emotional intelligence (EQ) and students' cognitive learning results of…

Learning in the Age of Networked Intelligence

ERIC Educational Resources Information Center

Tuomi, Ilkka

2007-01-01

The article presents ten theoretically substantiated "theses" on future education and learning, highlighting emerging trends that will shape educational systems. The focus is on the impact of innovation economy and knowledge society on learning. Specifically, the article elaborates the changing dynamics of production models since the first…

MENDEL: An Intelligent Computer Tutoring System for Genetics Problem-Solving, Conjecturing, and Understanding.

ERIC Educational Resources Information Center

Streibel, Michael; And Others

1987-01-01

Describes an advice-giving computer system being developed for genetics education called MENDEL that is based on research in learning, genetics problem solving, and expert systems. The value of MENDEL as a design tool and the tutorial function are stressed. Hypothesis testing, graphics, and experiential learning are also discussed. (Author/LRW)

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of the vision, intelligent adaptive cyber-physical ecosystems need to be developed to facilitate collaboration between the various stakeholders of engineering education, and to accelerate the development of a skilled engineering workforce. The major components of the ecosystems include integrated knowledge discovery and exploitation facilities, blended learning and research spaces, novel ultra-intelligent software agents, multimodal and autonomous interfaces, and networked cognitive and tele-presence robots.

Machine learning in updating predictive models of planning and scheduling transportation projects

DOT National Transportation Integrated Search

1997-01-01

A method combining machine learning and regression analysis to automatically and intelligently update predictive models used in the Kansas Department of Transportations (KDOTs) internal management system is presented. The predictive models used...

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.

PubMed

Tian, Shu; Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

PubMed Central

Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness. PMID:26693249

Design of Intelligent Robot as A Tool for Teaching Media Based on Computer Interactive Learning and Computer Assisted Learning to Improve the Skill of University Student

NASA Astrophysics Data System (ADS)

Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.

2018-01-01

The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.

Learning comunication strategies for distributed artificial intelligence

NASA Astrophysics Data System (ADS)

Kinney, Michael; Tsatsoulis, Costas

1992-08-01

We present a methodology that allows collections of intelligent system to automatically learn communication strategies, so that they can exchange information and coordinate their problem solving activity. In our methodology communication between agents is determined by the agents themselves, which consider the progress of their individual problem solving activities compared to the communication needs of their surrounding agents. Through learning, communication lines between agents might be established or disconnected, communication frequencies modified, and the system can also react to dynamic changes in the environment that might force agents to cease to exist or to be added. We have established dynamic, quantitative measures of the usefulness of a fact, the cost of a fact, the work load of an agent, and the selfishness of an agent (a measure indicating an agent's preference between transmitting information versus performing individual problem solving), and use these values to adapt the communication between intelligent agents. In this paper we present the theoretical foundations of our work together with experimental results and performance statistics of networks of agents involved in cooperative problem solving activities.

Connecting Multiple Intelligences through Open and Distance Learning: Going towards a Collective Intelligence?

ERIC Educational Resources Information Center

Medeiros Vieira, Leandro Mauricio; Ferasso, Marcos; Schröeder, Christine da Silva

2014-01-01

This theoretical essay is a learning approach reflexion on Howard Gardner's Theory of Multiple Intelligences and the possibilities provided by the education model known as open and distance learning. Open and distance learning can revolutionize traditional pedagogical practice, meeting the needs of those who have different forms of cognitive…

Addressing Diverse Learner Preferences and Intelligences with Emerging Technologies: Matching Models to Online Opportunities

ERIC Educational Resources Information Center

Zhang, Ke; Bonk, Curtis J.

2008-01-01

This paper critically reviews various learning preferences and human intelligence theories and models with a particular focus on the implications for online learning. It highlights a few key models, Gardner's multiple intelligences, Fleming and Mills' VARK model, Honey and Mumford's Learning Styles, and Kolb's Experiential Learning Model, and…

The Representation of Motor (Inter)action, States of Action, and Learning: Three Perspectives on Motor Learning by Way of Imagery and Execution

PubMed Central

Frank, Cornelia; Schack, Thomas

2017-01-01

Learning in intelligent systems is a result of direct and indirect interaction with the environment. While humans can learn by way of different states of (inter)action such as the execution or the imagery of an action, their unique potential to induce brain- and mind-related changes in the motor action system is still being debated. The systematic repetition of different states of action (e.g., physical and/or mental practice) and their contribution to the learning of complex motor actions has traditionally been approached by way of performance improvements. More recently, approaches highlighting the role of action representation in the learning of complex motor actions have evolved and may provide additional insight into the learning process. In the present perspective paper, we build on brain-related findings and sketch recent research on learning by way of imagery and execution from a hierarchical, perceptual-cognitive approach to motor control and learning. These findings provide insights into the learning of intelligent systems from a perceptual-cognitive, representation-based perspective and as such add to our current understanding of action representation in memory and its changes with practice. Future research should build bridges between approaches in order to more thoroughly understand functional changes throughout the learning process and to facilitate motor learning, which may have particular importance for cognitive systems research in robotics, rehabilitation, and sports. PMID:28588510

Combining metric episodes with semantic event concepts within the Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS)

NASA Astrophysics Data System (ADS)

Kelley, Troy D.; McGhee, S.

2013-05-01

This paper describes the ongoing development of a robotic control architecture that inspired by computational cognitive architectures from the discipline of cognitive psychology. The Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS) combines symbolic and sub-symbolic representations of knowledge into a unified control architecture. The new architecture leverages previous work in cognitive architectures, specifically the development of the Adaptive Character of Thought-Rational (ACT-R) and Soar. This paper details current work on learning from episodes or events. The use of episodic memory as a learning mechanism has, until recently, been largely ignored by computational cognitive architectures. This paper details work on metric level episodic memory streams and methods for translating episodes into abstract schemas. The presentation will include research on learning through novelty and self generated feedback mechanisms for autonomous systems.

Machine learning based Intelligent cognitive network using fog computing

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

Vision Guided Intelligent Robot Design And Experiments

NASA Astrophysics Data System (ADS)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

Simulated Classrooms and Artificial Students: The Potential Effects of New Technologies on Teacher Education.

ERIC Educational Resources Information Center

Brown, Abbie Howard

1999-01-01

Describes and discusses how simulation activities can be used in teacher education to augment the traditional field-experience approach, focusing on artificial intelligence, virtual reality, and intelligent tutoring systems. Includes an overview of simulation as a teaching and learning strategy and specific examples of high-technology simulations…

Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning

ERIC Educational Resources Information Center

Santos, Olga C.

2016-01-01

This paper argues that the research field of Artificial Intelligence in Education (AIED) can benefit from integrating recent technological advances (e.g., wearable devices, big data processing, 3D modelling, 3D printing, ambient intelligence) and design methodologies, such as TORMES, when developing systems that address the psychomotor learning…

The achievement of spacecraft autonomy through the thematic application of multiple cooperating intelligent agents

NASA Technical Reports Server (NTRS)

Rossomando, Philip J.

1992-01-01

A description is given of UNICORN, a prototype system developed for the purpose of investigating artificial intelligence (AI) concepts supporting spacecraft autonomy. UNICORN employs thematic reasoning, of the type first described by Rodger Schank of Northwestern University, to allow the context-sensitive control of multiple intelligent agents within a blackboard based environment. In its domain of application, UNICORN demonstrates the ability to reason teleologically with focused knowledge. Also presented are some of the lessons learned as a result of this effort. These lessons apply to any effort wherein system level autonomy is the objective.

A new intrusion prevention model using planning knowledge graph

NASA Astrophysics Data System (ADS)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Learning as a Problem Solving Tool. Technical Report CS74018-R.

ERIC Educational Resources Information Center

Claybrook, Billy G.

This paper explores the use of learning as a practical tool in problem solving. The idea that learning should and eventually will be a vital component of most Artificial Intelligence programs is pursued. Current techniques in learning systems are compared. A detailed discussion of the problems of representing, modifying, and creating heuristics is…

Strategies for the Creation, Design and Implementation of Effective Interactive Computer-Aided Learning Software in Numerate Business Subjects--The Byzantium Experience.

ERIC Educational Resources Information Center

Wilkinson-Riddle, G. J.; Patel, Ashok

1998-01-01

Discusses courseware development, including intelligent tutoring systems, under the Teaching and Learning Technology Programme and the Byzantium project that was designed to define computer-aided learning performance standards suitable for numerate business subjects; examine reasons to use computer-aided learning; and improve access to educational…

Development of an Inquiry-Based Learning Support System Based on an Intelligent Knowledge Exploration Approach

ERIC Educational Resources Information Center

Wu, Ji-Wei; Tseng, Judy C. R.; Hwang, Gwo-Jen

2015-01-01

Inquiry-Based Learning (IBL) is an effective approach for promoting active learning. When inquiry-based learning is incorporated into instruction, teachers provide guiding questions for students to actively explore the required knowledge in order to solve the problems. Although the World Wide Web (WWW) is a rich knowledge resource for students to…

The desktop interface in intelligent tutoring systems

NASA Technical Reports Server (NTRS)

Baudendistel, Stephen; Hua, Grace

1987-01-01

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine.

IVHS Institutional Issues and Case Studies, Analysis and Lessons Learned, Final Report

DOT National Transportation Integrated Search

1994-04-01

This 'Analysis and Lessons Learned' report contains observations, conclusions, and recommendations based on the performance of six case studies of Intelligent Vehicle-Highway Systems (IVHS) projects. Information to support the development of the case...

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

PubMed

Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

2018-02-01

Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising approaches for the prescription and monitoring of hemodialysis therapy. Current dialysis machines are continuously improving due to innovative technological developments, but patient safety is still a key challenge. Real-time monitoring systems, coupled with automatic instantaneous biofeedback, will allow changing dialysis prescriptions continuously. The integration of vital sign monitoring with dialysis parameters will produce large data sets that will require the use of data analysis techniques, possibly from the area of machine learning, in order to make better decisions and increase the safety of patients.

Reformulating Testing to Measure Thinking and Learning. Technical Report No. 6898.

ERIC Educational Resources Information Center

Collins, Allan

This paper discusses systemic problems with testing and outlines two scenarios for reformulating testing based on intelligent tutoring systems. Five desiderata are provided to underpin the type of testing proposed: (1) tests should emphasize learning and thinking; (2) tests should require generation as well as selection; (3) tests should be…

A learning-based agent for home neurorehabilitation.

PubMed

Lydakis, Andreas; Meng, Yuanliang; Munroe, Christopher; Wu, Yi-Ning; Begum, Momotaz

2017-07-01

This paper presents the iterative development of an artificially intelligent system to promote home-based neurorehabilitation. Although proper, structured practice of rehabilitation exercises at home is the key to successful recovery of motor functions, there is no home-program out there which can monitor a patient's exercise-related activities and provide corrective feedback in real time. To this end, we designed a Learning from Demonstration (LfD) based home-rehabilitation framework that combines advanced robot learning algorithms with commercially available wearable technologies. The proposed system uses exercise-related motion information and electromyography signals (EMG) of a patient to train a Markov Decision Process (MDP). The trained MDP model can enable an agent to serve as a coach for a patient. On a system level, this is the first initiative, to the best of our knowledge, to employ LfD in an health-care application to enable lay users to program an intelligent system. From a rehabilitation research perspective, this is a completely novel initiative to employ machine learning to provide interactive corrective feedback to a patient in home settings.

Computational intelligence in gait research: a perspective on current applications and future challenges.

PubMed

Lai, Daniel T H; Begg, Rezaul K; Palaniswami, Marimuthu

2009-09-01

Our mobility is an important daily requirement so much so that any disruption to it severely degrades our perceived quality of life. Studies in gait and human movement sciences, therefore, play a significant role in maintaining the well-being of our mobility. Current gait analysis involves numerous interdependent gait parameters that are difficult to adequately interpret due to the large volume of recorded data and lengthy assessment times in gait laboratories. A proposed solution to these problems is computational intelligence (CI), which is an emerging paradigm in biomedical engineering most notably in pathology detection and prosthesis design. The integration of CI technology in gait systems facilitates studies in disorders caused by lower limb defects, cerebral disorders, and aging effects by learning data relationships through a combination of signal processing and machine learning techniques. Learning paradigms, such as supervised learning, unsupervised learning, and fuzzy and evolutionary algorithms, provide advanced modeling capabilities for biomechanical systems that in the past have relied heavily on statistical analysis. CI offers the ability to investigate nonlinear data relationships, enhance data interpretation, design more efficient diagnostic methods, and extrapolate model functionality. These are envisioned to result in more cost-effective, efficient, and easy-to-use systems, which would address global shortages in medical personnel and rising medical costs. This paper surveys current signal processing and CI methodologies followed by gait applications ranging from normal gait studies and disorder detection to artificial gait simulation. We review recent systems focusing on the existing challenges and issues involved in making them successful. We also examine new research in sensor technologies for gait that could be combined with these intelligent systems to develop more effective healthcare solutions.

Building machines that learn and think like people.

PubMed

Lake, Brenden M; Ullman, Tomer D; Tenenbaum, Joshua B; Gershman, Samuel J

2017-01-01

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.

Emotional Intelligence among Auditory, Reading, and Kinesthetic Learning Styles of Elementary School Students in Ambon-Indonesia

ERIC Educational Resources Information Center

Leasa, Marleny; Corebima, Aloysius D.; Ibrohim; Suwono, Hadi

2017-01-01

Students have unique ways in managing the information in their learning process. VARK learning styles associated with memory are considered to have an effect on emotional intelligence. This quasi-experimental research was conducted to compare the emotional intelligence among the students having auditory, reading, and kinesthetic learning styles in…

Social learning and evolution: the cultural intelligence hypothesis

PubMed Central

van Schaik, Carel P.; Burkart, Judith M.

2011-01-01

If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer. PMID:21357223

Social learning and evolution: the cultural intelligence hypothesis.

PubMed

van Schaik, Carel P; Burkart, Judith M

2011-04-12

If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer.

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

NASA Astrophysics Data System (ADS)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

Emotional Intelligence Profiles and Learning Strategies in Secondary School Students

ERIC Educational Resources Information Center

Inglés, Cándido J.; Martínez-Monteagudo, María C.; Pérez Fuentes, Maria C.; García-Fernández, José M.; Molero, María del Mar; Suriá-Martinez, Raquel; Gázquez, José J.

2017-01-01

The aim of this study was to analyse the relationship among emotional intelligence (EI) and learning strategies, identifying different emotional intelligence profiles and determining possible statistically significant differences in learning strategies through the identified profiles. Thousand and seventy-one Spaniards secondary school students…

The Artificial Intelligence Applications to Learning Programme.

ERIC Educational Resources Information Center

Williams, Noel

1992-01-01

Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

The Nature of Intelligence and Its Relation to Learning.

ERIC Educational Resources Information Center

Jensen, Arthur R.

1979-01-01

The author presents intelligence and learning as theoretically and empirically separate concepts. Examining Spearman's "g" factor and the evolution, phylogeny and psychometrics of intelligence, he concludes that "g" is of dominant importance in scholastic learning. He notes some implications for equal educational opportunity.…

ISTAR: Intelligent System for Telemetry Analysis in Real-time

NASA Technical Reports Server (NTRS)

Simmons, Charles

1994-01-01

The intelligent system for telemetry analysis in real-time (ISTAR) is an advanced vehicle monitoring environment incorporating expert systems, analysis tools, and on-line hypermedia documentation. The system was developed for the Air Force Space and Missile Systems Center (SMC) in Los Angeles, California, in support of the inertial upper stage (IUS) booster vehicle. Over a five year period the system progressed from rapid prototype to operational system. ISTAR has been used to support five IUS missions and countless mission simulations. There were a significant number of lessons learned with respect to integrating an expert system capability into an existing ground system.

A Symposium: Relevant Cue Research, a Program of Systematic Evaluation: Considerations for Sustaining Instructional Design Research Using an Integrated Learning System.

ERIC Educational Resources Information Center

Grabowski, Barbara

An intelligent videodisc system on which comprehensive instructional development research can be conducted has been developed. This integrated learning system combines all other existing media, except objects, using a videodisc, microcomputer, printer, single monitor, hard disc storage with CPU for random access digitized audio, and headphones.…

Land mobile radio system phase I pilot report

DOT National Transportation Integrated Search

2003-12-15

This report presents an executive summary, the project overview, Intelligent Transportation System standards and lessons learned for implementation of an Integrated Voice and Data, Land Mobile Radio System (ITS technologies for the Alaska Department ...

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

PubMed

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intelligence Level Performance Standards Research for Autonomous Vehicles

PubMed Central

Bostelman, Roger B.; Hong, Tsai H.; Messina, Elena

2017-01-01

United States and European safety standards have evolved to protect workers near Automatic Guided Vehicles (AGV’s). However, performance standards for AGV’s and mobile robots have only recently begun development. Lessons can be learned from research and standards efforts for mobile robots applied to emergency response and military applications. Research challenges, tests and evaluations, and programs to develop higher intelligence levels for vehicles can also used to guide industrial AGV developments towards more adaptable and intelligent systems. These other efforts also provide useful standards development criteria for AGV performance test methods. Current standards areas being considered for AGVs are for docking, navigation, obstacle avoidance, and the ground truth systems that measure performance. This paper provides a look to the future with standards developments in both the performance of vehicles and the dynamic perception systems that measure intelligent vehicle performance. PMID:28649189

Intelligence Level Performance Standards Research for Autonomous Vehicles.

PubMed

Bostelman, Roger B; Hong, Tsai H; Messina, Elena

2015-01-01

United States and European safety standards have evolved to protect workers near Automatic Guided Vehicles (AGV's). However, performance standards for AGV's and mobile robots have only recently begun development. Lessons can be learned from research and standards efforts for mobile robots applied to emergency response and military applications. Research challenges, tests and evaluations, and programs to develop higher intelligence levels for vehicles can also used to guide industrial AGV developments towards more adaptable and intelligent systems. These other efforts also provide useful standards development criteria for AGV performance test methods. Current standards areas being considered for AGVs are for docking, navigation, obstacle avoidance, and the ground truth systems that measure performance. This paper provides a look to the future with standards developments in both the performance of vehicles and the dynamic perception systems that measure intelligent vehicle performance.

Facilitating Multiple Intelligences through Multimodal Learning Analytics

ERIC Educational Resources Information Center

Perveen, Ayesha

2018-01-01

This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner's 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as…

The Intelligent Method of Learning

ERIC Educational Resources Information Center

Moula, Alireza; Mohseni, Simin; Starrin, Bengt; Scherp, Hans Ake; Puddephatt, Antony J.

2010-01-01

Early psychologist William James [1842-1910] and philosopher John Dewey [1859-1952] described intelligence as a method which can be learned. That view of education is integrated with knowledge about the brain's executive functions to empower pupils to intelligently organize their learning. This article links the pragmatist philosophy of…

The Challenges of Human-Autonomy Teaming

NASA Technical Reports Server (NTRS)

Vera, Alonso

2017-01-01

Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.

Battlefield Management System: Data Requirements to Support Passage of Company Level Tactical Information.

DTIC Science & Technology

1987-03-01

intelligent way, assemble those documents and data in usable formats, examine the communications tapes available for this project, and to develop a sampling...Lifetime Learning Publications, Belmont. CA. 1982. Rowe. Neil C.. Artifcial Intelligence , Draft Copv, Class Notes for Winter Quarter. CS 33 10, \\aval...AT2 122 BATTLEFIELD MANAGEMENT SYSTEM DATA REQUIRENTS TO 1/2 SUPPORT PASSAGE OF COMPANY LEVEL TACTICAL INFORMATION (U) NVALE POSTGRADUATE SCHOOL

Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System

PubMed Central

Adelson, David; Brown, Fred; Chaudhri, Naeem

2017-01-01

The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice. PMID:28812013

Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System.

PubMed

Banjar, Haneen; Adelson, David; Brown, Fred; Chaudhri, Naeem

2017-01-01

The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice.

Personalized Intelligent Mobile Learning System for Supporting Effective English Learning

ERIC Educational Resources Information Center

Chen, Chih-Ming; Hsu, Shih-Hsun

2008-01-01

Since English has been an international language, how to enhance English levels of people by useful computer assisted learning forms or tools is a critical issue in non-English speaking countries because it definitely affects the overall competition ability of a country. With the rapid growth of wireless and mobile technologies, the mobile…

Architectures for Distributed and Complex M-Learning Systems: Applying Intelligent Technologies

ERIC Educational Resources Information Center

Caballe, Santi, Ed.; Xhafa, Fatos, Ed.; Daradoumis, Thanasis, Ed.; Juan, Angel A., Ed.

2009-01-01

Over the last decade, the needs of educational organizations have been changing in accordance with increasingly complex pedagogical models and with the technological evolution of e-learning environments with very dynamic teaching and learning requirements. This book explores state-of-the-art software architectures and platforms used to support…

Intelligent Agents for Dynamic Optimization of Learner Performances in an Online System

ERIC Educational Resources Information Center

Kamsa, Imane; Elouahbi, Rachid; El Khoukhi, Fatima

2017-01-01

Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environment, the learner is mostly affected by these…

Representing System Behaviors and Expert Behaviors for Intelligent Tutoring

DTIC Science & Technology

1987-02-09

Learned .................................. 44 . Future Directions ................................... 47 Sum m ary...and training environments to assist the instructor in meeting the students’ learning needs. The first application of the IMTS will be in training...identifies and resolves learning deficiencies and minimizes unproductive practice time. Another decision made early in the planning phase was to place

What have we learned about intelligent transportation systems? Chapter 1, What have we learned about ITS? A synthesis

DOT National Transportation Integrated Search

2000-12-01

This study is concerned with what we have learned about ITS. But ITS is composed of many technologies and applications, some of which, it will be seen, are more successful than others. So, in a disaggregate manner, this study examines which ITS techn...

A Multi-Language System for Knowledge Extraction in E-Learning Videos

ERIC Educational Resources Information Center

Sood, Aparesh; Mittal, Ankush; Sarthi, Divya

2006-01-01

The existing multimedia software in E-Learning does not provide par excellence multimedia data service to the common user, hence E-Learning services are still short of intelligence and sophisticated end user tools for visualization and retrieval. An efficient approach to achieve the tasks such as, regional language narration, regional language…

Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation

ERIC Educational Resources Information Center

Farzaneh, Mandana; Vanani, Iman Raeesi; Sohrabi, Babak

2012-01-01

E-learning is one of the most important learning approaches within which intelligent software agents can be efficiently used so as to automate and facilitate the process of learning. The aim of this paper is to illustrate a comprehensive categorization of intelligent software agent features, which is valuable for being deployed in the virtual…

Comparison of learning models based on mathematics logical intelligence in affective domain

NASA Astrophysics Data System (ADS)

Widayanto, Arif; Pratiwi, Hasih; Mardiyana

2018-04-01

The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

Scheduling lessons learned from the Autonomous Power System

NASA Technical Reports Server (NTRS)

Ringer, Mark J.

1992-01-01

The Autonomous Power System (APS) project at NASA LeRC is designed to demonstrate the applications of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The AIPS scheduler was tested within the APS system. This scheduler is able to efficiently assign available power to the requesting activities and share this information with other software agents within the APS system in order to implement the generated schedule. The AIPS scheduler is also able to cooperatively recover from fault situations by rescheduling the affected loads on the Brassboard in conjunction with the APEX FDIR system. AIPS served as a learning tool and an initial scheduling testbed for the integration of FDIR and automated scheduling systems. Many lessons were learned from the AIPS scheduler and are now being integrated into a new scheduler called SCRAP (Scheduler for Continuous Resource Allocation and Planning). This paper will service three purposes: an overview of the AIPS implementation, lessons learned from the AIPS scheduler, and a brief section on how these lessons are being applied to the new SCRAP scheduler.

Writing Pal: Feasibility of an Intelligent Writing Strategy Tutor in the High School Classroom

ERIC Educational Resources Information Center

Roscoe, Rod D.; McNamara, Danielle S.

2013-01-01

The Writing Pal (W-Pal) is a novel intelligent tutoring system (ITS) that offers writing strategy instruction, game-based practice, essay writing practice, and formative feedback to developing writers. Compared to more tractable and constrained learning domains for ITS, writing is an ill-defined domain because the features of effective writing are…

Multiple Intelligences, Motivations and Learning Experience Regarding Video-Assisted Subjects in a Rural University

ERIC Educational Resources Information Center

Hajhashemi, Karim; Caltabiano, Nerina; Anderson, Neil; Tabibzadeh, Seyed Asadollah

2018-01-01

This study investigates multiple intelligences in relation to online video experiences, age, gender, and mode of learning from a rural Australian university. The inter-relationships between learners' different intelligences and their motivations and learning experience with the supplementary online videos utilised in their subjects are…

IS Learning: The Impact of Gender and Team Emotional Intelligence

ERIC Educational Resources Information Center

Dunaway, Mary M.

2013-01-01

In university settings, dysfunction in teamwork often challenges problem-based learning in IS projects. Researchers of IS Education have largely overlooked Team Emotional Intelligence (TEI), which offers a collective cognitive skill that may benefit the student learning experience. Hypothesized are four dimensions of emotional intelligence (EI)…

Intelligence moderates reinforcement learning: a mini-review of the neural evidence

PubMed Central

2014-01-01

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. PMID:25185818

Intelligence moderates reinforcement learning: a mini-review of the neural evidence.

PubMed

Chen, Chong

2015-06-01

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. Copyright © 2015 the American Physiological Society.

The future of radiology augmented with Artificial Intelligence: A strategy for success.

PubMed

Liew, Charlene

2018-05-01

The rapid development of Artificial Intelligence/deep learning technology and its implementation into routine clinical imaging will cause a major transformation to the practice of radiology. Strategic positioning will ensure the successful transition of radiologists into their new roles as augmented clinicians. This paper describes an overall vision on how to achieve a smooth transition through the practice of augmented radiology where radiologists-in-the-loop ensure the safe implementation of Artificial Intelligence systems. Copyright © 2018 Elsevier B.V. All rights reserved.

The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.

PubMed

Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

2015-01-01

The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.

The Prediction of Students’ Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning

PubMed Central

Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

2015-01-01

The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school. PMID:26435760

Pathways of Learning: Teaching Students and Parents about Multiple Intelligences.

ERIC Educational Resources Information Center

Lazear, David

This book is concerned with reinventing the learning process from a multiple intelligences perspective and urges explicitly teaching students about multiple intelligences to further their metacognitive understanding. The multiple-intelligence-based curriculum is intended to interface with the regular academic curriculum. An introductory chapter…

DYNACLIPS (DYNAmic CLIPS): A dynamic knowledge exchange tool for intelligent agents

NASA Technical Reports Server (NTRS)

Cengeloglu, Yilmaz; Khajenoori, Soheil; Linton, Darrell

1994-01-01

In a dynamic environment, intelligent agents must be responsive to unanticipated conditions. When such conditions occur, an intelligent agent may have to stop a previously planned and scheduled course of actions and replan, reschedule, start new activities and initiate a new problem solving process to successfully respond to the new conditions. Problems occur when an intelligent agent does not have enough knowledge to properly respond to the new situation. DYNACLIPS is an implementation of a framework for dynamic knowledge exchange among intelligent agents. Each intelligent agent is a CLIPS shell and runs a separate process under SunOS operating system. Intelligent agents can exchange facts, rules, and CLIPS commands at run time. Knowledge exchange among intelligent agents at run times does not effect execution of either sender and receiver intelligent agent. Intelligent agents can keep the knowledge temporarily or permanently. In other words, knowledge exchange among intelligent agents would allow for a form of learning to be accomplished.

A review of intelligent systems for heart sound signal analysis.

PubMed

Nabih-Ali, Mohammed; El-Dahshan, El-Sayed A; Yahia, Ashraf S

2017-10-01

Intelligent computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. CAD systems could provide physicians with a suggestion about the diagnostic of heart diseases. The objective of this paper is to review the recent published preprocessing, feature extraction and classification techniques and their state of the art of phonocardiogram (PCG) signal analysis. Published literature reviewed in this paper shows the potential of machine learning techniques as a design tool in PCG CAD systems and reveals that the CAD systems for PCG signal analysis are still an open problem. Related studies are compared to their datasets, feature extraction techniques and the classifiers they used. Current achievements and limitations in developing CAD systems for PCG signal analysis using machine learning techniques are presented and discussed. In the light of this review, a number of future research directions for PCG signal analysis are provided.

Multisensor system and artificial intelligence in housing for the elderly.

PubMed

Chan, M; Bocquet, H; Campo, E; Val, T; Estève, D; Pous, J

1998-01-01

To improve the safety of a growing proportion of elderly and disabled people in the developed countries, a multisensor system based on Artificial Intelligence (AI), Advanced Telecommunications (AT) and Information Technology (IT) has been devised and fabricated. Thus, the habits and behaviours of these populations will be recorded without disturbing their daily activities. AI will diagnose any abnormal behavior or change and the system will warn the professionals. Gerontology issues are presented together with the multisensor system, the AI-based learning and diagnosis methodology and the main functionalities.

Intelligent Control Systems Research

NASA Technical Reports Server (NTRS)

Loparo, Kenneth A.

1994-01-01

Results of a three phase research program into intelligent control systems are presented. The first phase looked at implementing the lowest or direct level of a hierarchical control scheme using a reinforcement learning approach assuming no a priori information about the system under control. The second phase involved the design of an adaptive/optimizing level of the hierarchy and its interaction with the direct control level. The third and final phase of the research was aimed at combining the results of the previous phases with some a priori information about the controlled system.

Modelling intelligent behavior

NASA Technical Reports Server (NTRS)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

NASA Astrophysics Data System (ADS)

Nieten, Joseph L.; Burke, Roger

1993-03-01

The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

Learning Intercultural Communication Skills with Virtual Humans: Feedback and Fidelity

ERIC Educational Resources Information Center

Lane, H. Chad; Hays, Matthew Jensen; Core, Mark G.; Auerbach, Daniel

2013-01-01

In the context of practicing intercultural communication skills, we investigated the role of fidelity in a game-based, virtual learning environment as well as the role of feedback delivered by an intelligent tutoring system. In 2 experiments, we compared variations on the game interface, use of the tutoring system, and the form of the feedback.…

What have we learned about intelligent transportation systems?

DOT National Transportation Integrated Search

2000-12-01

This study is concerned with what we have learned about ITS. But ITS is composed of many technologies and applications, some of which, it will be seen, are more successful than others. So, in a disaggregate manner, this study examines which ITS techn...

The Relationship between Emotional Intelligence and Productive Language Skills

ERIC Educational Resources Information Center

Genç, Gülten; Kulusakh, Emine; Aydin, Savas

2016-01-01

Emotional intelligence has recently attracted educators' attention around the world. Educators who try to investigate the factors in language learning achievement have decided to pave the way to success through emotional intelligence. The relationship between emotional intelligence and language learning is the major concern of this study. The…

The specificity of parenting effects: Differential relations of parent praise and criticism to children's theories of intelligence and learning goals.

PubMed

Gunderson, Elizabeth A; Donnellan, M Brent; Robins, Richard W; Trzesniewski, Kali H

2018-04-24

Individuals who believe that intelligence can be improved with effort (an incremental theory of intelligence) and who approach challenges with the goal of improving their understanding (a learning goal) tend to have higher academic achievement. Furthermore, parent praise is associated with children's incremental theories and learning goals. However, the influences of parental criticism, as well as different forms of praise and criticism (e.g., process vs. person), have received less attention. We examine these associations by analyzing two existing datasets (Study 1: N = 317 first to eighth graders; Study 2: N = 282 fifth and eighth graders). In both studies, older children held more incremental theories of intelligence, but lower learning goals, than younger children. Unexpectedly, the relation between theories of intelligence and learning goals was nonsignificant and did not vary with children's grade level. In both studies, overall perceived parent praise positively related to children's learning goals, whereas perceived parent criticism negatively related to incremental theories of intelligence. In Study 2, perceived parent process praise was the only significant (positive) predictor of children's learning goals, whereas perceived parent person criticism was the only significant (negative) predictor of incremental theories of intelligence. Finally, Study 2 provided some support for our hypothesis that age-related differences in perceived parent praise and criticism can explain age-related differences in children's learning goals. Results suggest that incremental theories of intelligence and learning goals might not be strongly related during childhood and that perceived parent praise and criticism have important, but distinct, relations with each motivational construct. Copyright © 2018 Elsevier Inc. All rights reserved.

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

NASA Astrophysics Data System (ADS)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.

Intelligent Image Based Computer Aided Education (IICAE)

NASA Astrophysics Data System (ADS)

David, Amos A.; Thiery, Odile; Crehange, Marion

1989-03-01

Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.

The effect of multiple intelligence-based learning towards students’ concept mastery and interest in learning matter

NASA Astrophysics Data System (ADS)

Pratiwi, W. N.; Rochintaniawati, D.; Agustin, R. R.

2018-05-01

This research was focused on investigating the effect of multiple intelligence -based learning as a learning approach towards students’ concept mastery and interest in learning matter. The one-group pre-test - post-test design was used in this research towards a sample which was according to the suitable situation of the research sample, n = 13 students of the 7th grade in a private school in Bandar Seri Begawan. The students’ concept mastery was measured using achievement test and given at the pre-test and post-test, meanwhile the students’ interest level was measured using a Likert Scale for interest. Based on the analysis of the data, the result shows that the normalized gain was .61, which was considered as a medium improvement. in other words, students’ concept mastery in matter increased after being taught using multiple intelligence-based learning. The Likert scale of interest shows that most students have a high interest in learning matter after being taught by multiple intelligence-based learning. Therefore, it is concluded that multiple intelligence – based learning helped in improving students’ concept mastery and gain students’ interest in learning matter.

A Comparison of Learning Environments: All That Glitters... Interim Technical Paper for Period January 1990-July 1991.

ERIC Educational Resources Information Center

Shute, Valerie J.

Aptitude-treatment interactions (ATIs) refer to the covariation between learner characteristic and instructional treatment in relation to some outcome measure. To systematically test for ATI, an intelligent tutoring system instructing in basic principles of electricity was chosen as a complex but controlled learning task. Two learning environments…

A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets

ERIC Educational Resources Information Center

Voß, Lydia; Schatten, Carlotta; Mazziotti, Claudia; Schmidt-Thieme, Lars

2015-01-01

Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

Cognitive Support Embedded in Self-Regulated E-Learning Systems for Students with Special Learning Needs

ERIC Educational Resources Information Center

Chatzara, K.; Karagiannidis, C.; Stamatis, D.

2016-01-01

This paper presents an anthropocentric approach in human-machine interaction in the area of self-regulated e-learning. In an attempt to enhance communication mediated through computers for pedagogical use we propose the incorporation of an intelligent emotional agent that is represented by a synthetic character with multimedia capabilities,…

Using Adaptive Learning Technologies to Personalize Instruction to Student Interests: The Impact of Relevant Contexts on Performance and Learning Outcomes

ERIC Educational Resources Information Center

Walkington, Candace A.

2013-01-01

Adaptive learning technologies are emerging in educational settings as a means to customize instruction to learners' background, experiences, and prior knowledge. Here, a technology-based personalization intervention within an intelligent tutoring system (ITS) for secondary mathematics was used to adapt instruction to students' personal interests.…

Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

NASA Technical Reports Server (NTRS)

Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

1992-01-01

A software application to assist end-users of the high burst rate (HBR) link evaluation terminal (LET) for satellite communications is being developed. The HBR LET system developed at NASA Lewis Research Center is an element of the Advanced Communications Technology Satellite (ACTS) Project. The HBR LET is divided into seven major subsystems, each with its own expert. Programming scripts, test procedures defined by design engineers, set up the HBR LET system. These programming scripts are cryptic, hard to maintain and require a steep learning curve. These scripts were developed by the system engineers who will not be available for the end-users of the system. To increase end-user productivity a friendly interface needs to be added to the system. One possible solution is to provide the user with adequate documentation to perform the needed tasks. With the complexity of this system the vast amount of documentation needed would be overwhelming and the information would be hard to retrieve. With limited resources, maintenance is another reason for not using this form of documentation. An advanced form of interaction is being explored using current computer techniques. This application, which incorporates a combination of multimedia and artificial intelligence (AI) techniques to provided end-users with an intelligent interface to the HBR LET system, is comprised of an intelligent assistant, intelligent tutoring, and hypermedia documentation. The intelligent assistant and tutoring systems address the critical programming needs of the end-user.

Using Collective Intelligence to Route Internet Traffic

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Frank, Jeremy

1998-01-01

A Collective Intelligence (COIN) is a community of interacting reinforcement learning (RL) algorithms designed so that their collective behavior maximizes a global utility function. We introduce the theory of COINs, then present experiments using that theory to design COINs to control internet traffic routing. These experiments indicate that COINs outperform previous RL-based systems for such routing that have previously been investigated.

Three Years of Intelligent Tutoring Evaluation: A Summary of Findings.

ERIC Educational Resources Information Center

Orey, Michael

Over the past 3 years, a variety of studies in intelligent tutoring system (ITS) effectiveness have been conducted. A summary is provided of the research into the use of POSIT, MALM, and the Mobile Subscriber Remote-Telephone Terminal (MSRT) Tutor. POSIT is an ITS for the tutoring of whole-number subtraction. It assumes that the learning of a…

An intelligent tutoring system that generates a natural language dialogue using dynamic multi-level planning.

PubMed

Woo, Chong Woo; Evens, Martha W; Freedman, Reva; Glass, Michael; Shim, Leem Seop; Zhang, Yuemei; Zhou, Yujian; Michael, Joel

2006-09-01

The objective of this research was to build an intelligent tutoring system capable of carrying on a natural language dialogue with a student who is solving a problem in physiology. Previous experiments have shown that students need practice in qualitative causal reasoning to internalize new knowledge and to apply it effectively and that they learn by putting their ideas into words. Analysis of a corpus of 75 hour-long tutoring sessions carried on in keyboard-to-keyboard style by two professors of physiology at Rush Medical College tutoring first-year medical students provided the rules used in tutoring strategies and tactics, parsing, and text generation. The system presents the student with a perturbation to the blood pressure, asks for qualitative predictions of the changes produced in seven important cardiovascular variables, and then launches a dialogue to correct any errors and to probe for possible misconceptions. The natural language understanding component uses a cascade of finite-state machines. The generation is based on lexical functional grammar. Results of experiments with pretests and posttests have shown that using the system for an hour produces significant learning gains and also that even this brief use improves the student's ability to solve problems more then reading textual material on the topic. Student surveys tell us that students like the system and feel that they learn from it. The system is now in regular use in the first-year physiology course at Rush Medical College. We conclude that the CIRCSIM-Tutor system demonstrates that intelligent tutoring systems can implement effective natural language dialogue with current language technology.

EFL Learners' Self-Perceived Strategy Use across Various Intelligence Types: A Case Study

ERIC Educational Resources Information Center

Tahriri, Abdorreza; Divsar, Hoda

2011-01-01

Increasing attention paid to learner-centered pedagogy in recent years has highlighted the examination of intelligence and language learning strategies (LLSs) among others. This study explores EFL learners' perceived use of language learning strategies across various intelligence types as reflected in Gardner's 1983 Multiple Intelligences Theory.…

AVID Students' Perceptions of Intelligence: A Mixed Methods Study

ERIC Educational Resources Information Center

Becker, John Darrell

2012-01-01

Students' perceptions of intelligence have been shown to have an effect on learning. Students who see intelligence as something that can be developed, those with a growth mindset, often experience academic success, while those who perceive intelligence to be a fixed entity are typically less likely to take on challenging learning experiences and…

Sensory Motor Coordination in Robonaut

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II

2003-01-01

As a participant of the year 2000 NASA Summer Faculty Fellowship Program, I worked with the engineers of the Dexterous Robotics Laboratory at NASA Johnson Space Center on the Robonaut project. The Robonaut is an articulated torso with two dexterous arms, left and right five-fingered hands, and a head with cameras mounted on an articulated neck. This advanced space robot, now driven only teleoperatively using VR gloves, sensors and helmets, is to be upgraded to a thinking system that can find, interact with and assist humans autonomously, allowing the Crew to work with Robonaut as a (junior) member of their team. Thus, the work performed this summer was toward the goal of enabling Robonaut to operate autonomously as an intelligent assistant to astronauts. Our underlying hypothesis is that a robot can develop intelligence if it learns a set of basic behaviors (i.e., reflexes - actions tightly coupled to sensing) and through experience learns how to sequence these to solve problems or to accomplish higher-level tasks. We describe our approach to the automatic acquisition of basic behaviors as learning sensory-motor coordination (SMC). Although research in the ontogenesis of animals development from the time of conception) supports the approach of learning SMC as the foundation for intelligent, autonomous behavior, we do not know whether it will prove viable for the development of autonomy in robots. The first step in testing the hypothesis is to determine if SMC can be learned by the robot. To do this, we have taken advantage of Robonaut's teleoperated control system. When a person teleoperates Robonaut, the person's own SMC causes the robot to act purposefully. If the sensory signals that the robot detects during teleoperation are recorded over several repetitions of the same task, it should be possible through signal analysis to identify the sensory-motor couplings that accompany purposeful motion. In this report, reasons for suspecting SMC as the basis for intelligent behavior will be reviewed. A robot control system for autonomous behavior that uses learned SMC will be proposed. Techniques for the extraction of salient parameters from sensory and motor data will be discussed. Experiments with Robonaut will be discussed and preliminary data presented.

Towards Methodologies for Building Knowledge-Based Instructional Systems.

ERIC Educational Resources Information Center

Duchastel, Philippe

1992-01-01

Examines the processes involved in building instructional systems that are based on artificial intelligence and hypermedia technologies. Traditional instructional systems design methodology is discussed; design issues including system architecture and learning strategies are addressed; and a new methodology for building knowledge-based…

Application of artificial intelligence to the management of urological cancer.

PubMed

Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

2007-10-01

Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

NASA Technical Reports Server (NTRS)

Wu, G. Gordon

1995-01-01

Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

NASA Technical Reports Server (NTRS)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Theories of Intelligence, Learning, and Motivation as a Basic Educational Praxis

ERIC Educational Resources Information Center

Van Hook, Steven R.

2008-01-01

This article begins with an examination of the early building blocks of intelligence and learning through signs and symbols, such as examined by Vygotsky and Freire. Then the inquiry moves into methods of achieving resonance as praxis of learning as expanded on by Freire, and connecting with students by addressing their multiple intelligences as…

Problem-Based Learning Pedagogies: Psychological Processes and Enhancement of Intelligences

ERIC Educational Resources Information Center

Tan, Oon-Seng

2007-01-01

Education in this 21st century is concerned with developing intelligences. Problem solving in real-world contexts involves multiple ways of knowing and learning. Intelligence in the real world involves not only learning how to do things effectively but also more importantly the ability to deal with novelty and growing our capacity to adapt, select…

Rose garden promises of intelligent tutoring systems: Blossom or thorn

NASA Technical Reports Server (NTRS)

Shute, Valerie J.

1991-01-01

Intelligent tutoring systems (ITS) have been in existence for over a decade. However, few controlled evaluation studies have been conducted comparing the effectiveness of these systems to more traditional instruction methods. Two main promises of ITSs are examined: (1) Engender more effective and efficient learning in relation to traditional formats; and (2) Reduce the range of learning outcome measures where a majority of individuals are elevated to high performance levels. Bloom (1984) has referred to these as the two sigma problem; to achieve two standard deviation improvements with tutoring over traditional instruction methods. Four ITSs are discussed in relation to the two promises. These tutors have undergone systematic, controlled evaluations: (1) The LISP tutor (Anderson Farrell and Sauers, 1984); (2) Smithtown (Shute and Glaser, in press); (3) Sherlock (Lesgold, Lajoie, Bunzo and Eggan, 1990); and (4) The Pascal ITS (Bonar, Cunningham, Beatty and Well, 1988). Results show that these four tutors do accelerate learning with no degradation in final outcome. Suggestions for improvements to the design and evaluation of ITSs are discussed.

A Voice-Based E-Examination Framework for Visually Impaired Students in Open and Distance Learning

ERIC Educational Resources Information Center

Azeta, Ambrose A.; Inam, Itorobong A.; Daramola, Olawande

2018-01-01

Voice-based systems allow users access to information on the internet over a voice interface. Prior studies on Open and Distance Learning (ODL) e-examination systems that make use of voice interface do not sufficiently exhibit intelligent form of assessment, which diminishes the rigor of examination. The objective of this paper is to improve on…

Intelligent Adaptable e-Assessment for Inclusive e-Learning

ERIC Educational Resources Information Center

Nacheva-Skopalik, Lilyana; Green, Steve

2016-01-01

Access to education is one of the main human rights. Everyone should have access to education and be capable of benefiting from it. However there are a number who are excluded, not because of a lack of ability but simply because they have a disability or specific need which current education systems do not address. A learning system in which…

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

NSF Support for Information Science Research.

ERIC Educational Resources Information Center

Brownstein, Charles N.

1986-01-01

Major research opportunities and needs are expected by the National Science Foundation in six areas of information science: models of adaptive information processing, learning, searching, and recognition; knowledge resource systems, particularly intelligent systems; user-system interaction; augmentation of human information processing tasks;…

Serious Use of a Serious Game for Language Learning

ERIC Educational Resources Information Center

Johnson, W. Lewis

2010-01-01

The Tactical Language and Culture Training System (TLCTS) helps learners acquire basic communicative skills in foreign languages and cultures. Learners acquire communication skills through a combination of interactive lessons and serious games. Artificial intelligence plays multiple roles in this learning environment: to process the learner's…

The foundations of plant intelligence.

PubMed

Trewavas, Anthony

2017-06-06

Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

The foundations of plant intelligence

PubMed Central

2017-01-01

Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses. PMID:28479977

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

In the Context of Multiple Intelligences Theory, Intelligent Data Analysis of Learning Styles Was Based on Rough Set Theory

ERIC Educational Resources Information Center

Narli, Serkan; Ozgen, Kemal; Alkan, Huseyin

2011-01-01

The present study aims to identify the relationship between individuals' multiple intelligence areas and their learning styles with mathematical clarity using the concept of rough sets which is used in areas such as artificial intelligence, data reduction, discovery of dependencies, prediction of data significance, and generating decision…

Contribution to Language Teaching and Learning: A Review of Emotional Intelligence

ERIC Educational Resources Information Center

Sucaromana, Usaporn

2012-01-01

The aim of this paper is to introduce the importance of emotional intelligence and the extent to which emotional intelligence can be implemented and used to improve language teaching and learning. Since emotional intelligence is perceived to play a crucial part in every aspect of people's lives, it can be extended to language teaching and…

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Duda, R. O.; Fikes, R. E.; Hart, P. E.; Nilsson, N. J.; Thorndyke, P. W.; Wilber, B. M.

1971-01-01

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

Cognitive Architectures and Autonomy: A Comparative Review

NASA Astrophysics Data System (ADS)

Thórisson, Kristinn; Helgasson, Helgi

2012-05-01

One of the original goals of artificial intelligence (AI) research was to create machines with very general cognitive capabilities and a relatively high level of autonomy. It has taken the field longer than many had expected to achieve even a fraction of this goal; the community has focused on building specific, targeted cognitive processes in isolation, and as of yet no system exists that integrates a broad range of capabilities or presents a general solution to autonomous acquisition of a large set of skills. Among the reasons for this are the highly limited machine learning and adaptation techniques available, and the inherent complexity of integrating numerous cognitive and learning capabilities in a coherent architecture. In this paper we review selected systems and architectures built expressly to address integrated skills. We highlight principles and features of these systems that seem promising for creating generally intelligent systems with some level of autonomy, and discuss them in the context of the development of future cognitive architectures. Autonomy is a key property for any system to be considered generally intelligent, in our view; we use this concept as an organizing principle for comparing the reviewed systems. Features that remain largely unaddressed in present research, but seem nevertheless necessary for such efforts to succeed, are also discussed.

Intelligent robot trends and predictions for the .net future

NASA Astrophysics Data System (ADS)

Hall, Ernest L.

2001-10-01

An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The use of these machines in factory automation can improve productivity, increase product quality and improve competitiveness. This paper presents a discussion of recent and future technical and economic trends. During the past twenty years the use of industrial robots that are equipped not only with precise motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. Intelligent robot products have been developed in many cases for factory automation and for some hospital and home applications. To reach an even higher degree of applications, the addition of learning may be required. Recently, learning theories such as the adaptive critic have been proposed. In this type of learning, a critic provides a grade to the controller of an action module such as a robot. The adaptive critic is a good model for human learning. In general, the critic may be considered to be the human with the teach pendant, plant manager, line supervisor, quality inspector or the consumer. If the ultimate critic is the consumer, then the quality inspector must model the consumer's decision-making process and use this model in the design and manufacturing operations. Can the adaptive critic be used to advance intelligent robots? Intelligent robots have historically taken decades to be developed and reduced to practice. Methods for speeding this development include technology such as rapid prototyping and product development and government, industry and university cooperation.

A reinforcement learning-based architecture for fuzzy logic control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

Performance improvement in remote manipulation with time delay by means of a learning system.

NASA Technical Reports Server (NTRS)

Freedy, A.; Weltman, G.

1973-01-01

A teleoperating system is presented that involves shared control between a human operator and a general-purpose computer-based learning machine. This setup features a trainable control network termed the autonomous control subsystem (ACS) which is able to observe the operator's control actions, learn the task at hand, and take appropriate control actions. A working ACS system is described that has been put in operation for the purpose of exploring the uses of a remote intelligence of this type. The expansion of the present system into a multifunctional learning machine capable of a greater degree of autonomy is also discussed.

Brief Report: Evaluation of an Intelligent Learning Environment for Young Children with Autism Spectrum Disorder.

PubMed

Zheng, Zhi; Warren, Zachary; Weitlauf, Amy; Fu, Qiang; Zhao, Huan; Swanson, Amy; Sarkar, Nilanjan

2016-11-01

Researchers are increasingly attempting to develop and apply innovative technological platforms for early detection and intervention of autism spectrum disorder (ASD). This pilot study designed and evaluated a novel technologically-mediated intelligent learning environment with relevance to early social orienting skills. The environment was endowed with the capacity to administer social orienting cues and adaptively respond to autonomous real-time measurement of performance (i.e., non-contact gaze measurement). We evaluated the system with both toddlers with ASD (n = 8) as well as typically developing infants (n = 8). Children in both groups were able to ultimately respond accurately to social prompts delivered by the technological system. Results also indicated that the system was capable of attracting and pushing toward correct performance autonomously without user intervention.

A Framework System for Intelligent Support in Open Distributed Learning Environments--A Look Back from 16 Years Later

ERIC Educational Resources Information Center

Hoppe, H. Ulrich

2016-01-01

The 1998 paper by Martin Mühlenbrock, Frank Tewissen, and myself introduced a multi-agent architecture and a component engineering approach for building open distributed learning environments to support group learning in different types of classroom settings. It took up prior work on "multiple student modeling" as a method to configure…

The Effects of Concept Map-Oriented Gesture-Based Teaching System on Learners' Learning Performance and Cognitive Load in Earth Science Course

ERIC Educational Resources Information Center

Hsieh, Sheng-Wen; Ho, Shu-Chun; Wu, Min-ping; Ni, Ci-Yuan

2016-01-01

Gesture-based learning have particularities, because learners interact in the learning process through the actual way, just like they interact in the nondigital world. It also can support kinesthetic pedagogical practices to benefit learners with strong bodily-kinesthetic intelligence. But without proper assistance or guidance, learners' learning…

An Intelligent Web-Based System for Diagnosing Student Learning Problems Using Concept Maps

ERIC Educational Resources Information Center

Acharya, Anal; Sinha, Devadatta

2017-01-01

The aim of this article is to propose a method for development of concept map in web-based environment for identifying concepts a student is deficient in after learning using traditional methods. Direct Hashing and Pruning algorithm was used to construct concept map. Redundancies within the concept map were removed to generate a learning sequence.…

Information Processing Approaches to Cognitive Development

DTIC Science & Technology

1989-08-04

O’Connor (Eds.), Intelligence and learning . New York: Plenum Press. Deloache, J.S. (1988). The development of representation in young chidren . In H.W...Klahr, D., & Carver, S.M. (1988). Cognitive objectives in a LOGO debugging curriculum: Instruction, Learning , and Transfer. Cognitive Psychology, 20...Production system models of learning and development. Cambridge, MA: MIT Press. TWO KINDS OF INFORMATION PROCESSING APPROACHES TO COGNITIVE DEVELOPMENT

The Role of Intelligence in Social Learning.

PubMed

Vostroknutov, Alexander; Polonio, Luca; Coricelli, Giorgio

2018-05-02

Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.

Intelligent tutoring systems as tools for investigating individual differences in learning

NASA Technical Reports Server (NTRS)

Shute, Valerie J.

1987-01-01

The ultimate goal of this research is to build an improved model-based selection and classification system for the United States Air Force. Researchers are developing innovative approaches to ability testing. The Learning Abilities Measurement Program (LAMP) examines individual differences in learning abilities, seeking answers to the questions of why some people learn more and better than others and whether there are basic cognitive processes applicable across tasks and domains that are predictive of successful performance (or whether there are more complex problem solving behaviors involved).

Conceptual Commitments of the LIDA Model of Cognition

NASA Astrophysics Data System (ADS)

Franklin, Stan; Strain, Steve; McCall, Ryan; Baars, Bernard

2013-06-01

Significant debate on fundamental issues remains in the subfields of cognitive science, including perception, memory, attention, action selection, learning, and others. Psychology, neuroscience, and artificial intelligence each contribute alternative and sometimes conflicting perspectives on the supervening problem of artificial general intelligence (AGI). Current efforts toward a broad-based, systems-level model of minds cannot await theoretical convergence in each of the relevant subfields. Such work therefore requires the formulation of tentative hypotheses, based on current knowledge, that serve to connect cognitive functions into a theoretical framework for the study of the mind. We term such hypotheses "conceptual commitments" and describe the hypotheses underlying one such model, the Learning Intelligent Distribution Agent (LIDA) Model. Our intention is to initiate a discussion among AGI researchers about which conceptual commitments are essential, or particularly useful, toward creating AGI agents.

STEPS: A Simulated, Tutorable Physics Student.

ERIC Educational Resources Information Center

Ur, Sigalit; VanLehn, Kurt

1995-01-01

Describes a simulated student that learns by interacting with a human tutor. Tests suggest that simulated students, when developed past the prototype stage, could be valuable for training human tutors. Provides a computational cognitive task analysis of the skill of learning from a tutor that is useful for designing intelligent tutoring systems.…

The Teaching and Learning Environment SAIDA: Some Features and Lessons.

ERIC Educational Resources Information Center

Grandbastien, Monique; Morinet-Lambert, Josette

Written in ADA language, SAIDA, a Help System for Data Implementation, is an experimental teaching and learning environment which uses artificial intelligence techniques to teach a computer science course on abstract data representations. The application domain is teaching advanced programming concepts which have not received much attention from…

A Semi-Automatic Approach to Construct Vietnamese Ontology from Online Text

ERIC Educational Resources Information Center

Nguyen, Bao-An; Yang, Don-Lin

2012-01-01

An ontology is an effective formal representation of knowledge used commonly in artificial intelligence, semantic web, software engineering, and information retrieval. In open and distance learning, ontologies are used as knowledge bases for e-learning supplements, educational recommenders, and question answering systems that support students with…

Learning by Communicating in Natural Language with Conversational Agents

ERIC Educational Resources Information Center

Graesser, Arthur; Li, Haiying; Forsyth, Carol

2014-01-01

Learning is facilitated by conversational interactions both with human tutors and with computer agents that simulate human tutoring and ideal pedagogical strategies. In this article, we describe some intelligent tutoring systems (e.g., AutoTutor) in which agents interact with students in natural language while being sensitive to their cognitive…

Improving Learning Object Quality: Moodle HEODAR Implementation

ERIC Educational Resources Information Center

Munoz, Carlos; Garcia-Penalvo, Francisco J.; Morales, Erla Mariela; Conde, Miguel Angel; Seoane, Antonio M.

2012-01-01

Automation toward efficiency is the aim of most intelligent systems in an educational context in which results calculation automation that allows experts to spend most of their time on important tasks, not on retrieving, ordering, and interpreting information. In this paper, the authors provide a tool that easily evaluates Learning Objects quality…

Artificial intelligence expert systems with neural network machine learning may assist decision-making for extractions in orthodontic treatment planning.

PubMed

Takada, Kenji

2016-09-01

New approach for the diagnosis of extractions with neural network machine learning. Seok-Ki Jung and Tae-Woo Kim. Am J Orthod Dentofacial Orthop 2016;149:127-33. Not reported. Mathematical modeling. Copyright © 2016 Elsevier Inc. All rights reserved.

Learning without Education. An Interview with Lewis J. Perelman. Background Briefing Paper.

ERIC Educational Resources Information Center

Easterling, Douglas

This interview with Lewis J. Perelman examines issues raised by his recent book, "School's Out" (1992), which describes the current educational system as an obsolete technology that is rapidly being replaced by the new metaprocess of hyperlearning. Hyperlearning will combine teaching and learning with artificial intelligence, broadband…

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

USGS Publications Warehouse

Albert, T.M.

1988-01-01

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

The relationship between learning styles, emotional social intelligence, and academic success of undergraduate nursing students.

PubMed

Suliman, Wafika A

2010-06-01

Feelings or emotions and thinking have been identified as forces that may affect one's learning styles (D. A. Kolb, 1984), emotional social intelligence, and success (R. Bar-On, 2004). This study on the relationship between academic success and the two variables of learning abilities or styles and emotional social intelligence was conducted at two colleges of nursing in Saudi Arabia. Both offer conventional and accelerated undergraduate nursing education programs. This study was designed to explore the preferred learning abilities or styles of Saudi nursing students in conventional and accelerated programs, the difference in emotional social intelligence between the two, and the relationships between academic success and learning styles and emotional social intelligence. A convenience sample was recruited, consisting of a total of 98 students, 50 and 48 of whom were enrolled, respectively, in conventional and accelerated programs. Self-administered instruments including the Kolb learning style inventory and the Bar-On emotional quotient inventory (EQ-i) were used to collect data, which were analyzed quantitatively. Both groups were found to favor a diverger style of learning, with total EQ-i scores showing no statistical difference between the two (t = 1.251, p =.214). "Self-regard" and "problem solving" earned the highest EQ-i content subscale scores for both groups. Pearson's correlation coefficient showed no significant relationship between learning abilities or styles and emotional social intelligence and academic success. The findings suggest that either no actual relationship exists or that emotional social intelligence may be confounded with factors such as professional and cultural values.

Cooperative intelligent robotics in space III; Proceedings of the Meeting, Boston, MA, Nov. 16-18, 1992

NASA Technical Reports Server (NTRS)

Erickson, Jon D. (Editor)

1992-01-01

The present volume on cooperative intelligent robotics in space discusses sensing and perception, Space Station Freedom robotics, cooperative human/intelligent robot teams, and intelligent space robotics. Attention is given to space robotics reasoning and control, ground-based space applications, intelligent space robotics architectures, free-flying orbital space robotics, and cooperative intelligent robotics in space exploration. Topics addressed include proportional proximity sensing for telerobots using coherent lasar radar, ground operation of the mobile servicing system on Space Station Freedom, teleprogramming a cooperative space robotic workcell for space stations, and knowledge-based task planning for the special-purpose dextrous manipulator. Also discussed are dimensions of complexity in learning from interactive instruction, an overview of the dynamic predictive architecture for robotic assistants, recent developments at the Goddard engineering testbed, and parallel fault-tolerant robot control.

Energizing the nursing lecture: Application of the Theory of Multiple Intelligence Learning.

PubMed

Amerson, Roxanne

2006-01-01

Nurse educators struggle to find ways to create learning opportunities that are interactive and appeal to the needs of various students. The key to energizing the nursing lecture is to create an environment that encourages students to be active participants. It is essential to use creativity to design cognitive strategies that appeal to students' learning preferences. This article discusses the methods one educator has used to implement the Theory of Multiple Intelligence Learning in the classroom. Specific cognitive strategies that address the learning preferences of each intelligence are discussed.

Interference and deception detection technology of satellite navigation based on deep learning

NASA Astrophysics Data System (ADS)

Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

2017-10-01

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

Agent-Based Learning Environments as a Research Tool for Investigating Teaching and Learning.

ERIC Educational Resources Information Center

Baylor, Amy L.

2002-01-01

Discusses intelligent learning environments for computer-based learning, such as agent-based learning environments, and their advantages over human-based instruction. Considers the effects of multiple agents; agents and research design; the use of Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) for instructional design for…

Intelligent systems engineering methodology

NASA Technical Reports Server (NTRS)

Fouse, Scott

1990-01-01

An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

Multiple Intelligences for Differentiated Learning

ERIC Educational Resources Information Center

Williams, R. Bruce

2007-01-01

There is an intricate literacy to Gardner's multiple intelligences theory that unlocks key entry points for differentiated learning. Using a well-articulated framework, rich with graphic representations, Williams provides a comprehensive discussion of multiple intelligences. He moves the teacher and students from curiosity, to confidence, to…

Do the Modern Neurosciences Call for a New Model of Organizational Cognition?

NASA Astrophysics Data System (ADS)

Seni, Dan Alexander

2012-10-01

Our purpose in this paper is to try to make a significant contribution to the analysis of cognitive capabilities of the organization of active social systems such as the business enterprise by re-examining the concepts of organizational intelligence, organizational memory and organizational learning in light of the findings of modern neuroscience. In fact, in this paper we propose that neuroscience shows that sociocognitivity is for real. In other words, cognition, in the broad sense, is not exclusive to living organisms: Certain kinds of social organizations (e.g. the enterprise) possess elementary cognitive capabilities by virtue of their structure and their functions. The classical theory of organizational cognition is the theory of Artificial Intelligence. We submit that this approach has proven to be false and barren, and that a materialist emergentist neuroscientific approach, in the tradition of Mario Bunge (2003, 2006), leads to a far more fruitful viewpoint, both for theory development and for eventual factual verification. Our proposals for sociocognitivity are based on findings in three areas of modern neuroscience and biopsychology: (1) The theory of intelligence and of intelligent systems; (2) The neurological theory of memory as distributed, hierarchical neuronal systems; (3) The theory of cognitive action in general and of learning in particular. We submit that findings in every one of these areas are applicable to the social organization.

A Cybernetic Design Methodology for 'Intelligent' Online Learning Support

NASA Astrophysics Data System (ADS)

Quinton, Stephen R.

The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.

The relationship between epistemological beliefs, implicit theories of intelligence, and self-regulated learning among Norwegian postsecondary students.

PubMed

Bråten, Ivar; Strømsø, Helge I

2005-12-01

More empirical work is needed to examine the dimensionality of personal epistemology and relations between those dimensions and motivational and strategic components of self-regulated learning. In particular, there is great need to investigate personal epistemology and its relation to self-regulated learning across cultures and academic contexts. Because the demarcation between personal epistemology and implicit theories of intelligence has been questioned, dimensions of personal epistemology should also be studied in relation to implicit theories of intelligence. The primary aim was to examine the dimensionality of personal epistemology and the relation between those dimensions and implicit theories of intelligence in the cultural context of Norwegian postsecondary education. A secondary aim was to examine the relative contribution of epistemological beliefs and theories of intelligence to motivational and strategic components of self-regulated learning in different academic contexts within that culture. The first sample included 178 business administration students in a traditional transmission-oriented instructional context; the second, 108 student teachers in an innovative pedagogical context. The dimensionality of the Schommer Epistemological Questionnaire was examined through factor analyses, and the resulting dimensions were examined in relation to implicit theories of intelligence. We performed multiple regression analyses, separately for the two academic contexts, to try to predict motivational (i.e. self-efficacy beliefs, mastery goal orientation, and interest) and strategic (i.e. self-regulatory strategy use) components of self-regulated learning with epistemological beliefs and implicit theories of intelligence. Considerable cross-cultural generalizability was found for the dimensionality of personal epistemology. Moreover, the dimensions of personal epistemology seemed to represent constructs separate from the construct of implicit theories of intelligence. Differences in the predictability of the epistemological dimensions were found for the two samples. For the student teachers, belief about knowledge construction and modification was a better predictor of self-regulated learning. For the business administration students, belief about the certainty of knowledge played a more important role in self-regulated learning. Epistemological beliefs predict self-regulated learning among Norwegian postsecondary students and play more important roles than implicit theories of intelligence. Relations between epistemological beliefs and self-regulated learning may vary with academic context.

A Common Cockpit Training System

DTIC Science & Technology

2005-01-01

a learning environment where students can practice ASW via free - play simulated tactical situations while receiving feedback and instruction customized...Mission Display and includes free play simulation capability to maximize training. This intelligent tutoring system (ITS) will observe the operator’s

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

NASA Technical Reports Server (NTRS)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

Leading to Learning and Competitive Intelligence

ERIC Educational Resources Information Center

Luu, Trong Tuan

2013-01-01

Purpose: This research aims to examine whether there is the chain effect from corporate social responsibility (CSR) and emotional intelligence (EI) to organizational learning and competitive intelligence in chemical companies in a Vietnam business setting. Design/methodology/approach: Structural equation modeling (SEM) approach was used to analyze…

A Study of the Relationship between Iranian EFL Learners' Level of Spatial Intelligence and Their Performance on Analytical and Perceptual Cloze Tests

ERIC Educational Resources Information Center

Ahmadian, Moussa; Jalilian, Vahid

2012-01-01

During the last two decades, Gardner's theory of multiple intelligences with its emphasis on learner variables has been appreciated in language learning. Spatial intelligence, as one domain of the multiple structures of intelligence, which is thought to play a great role in reading, writing, and literacy, particularly in L2 learning, has not…

Studies on a Novel Neuro-dynamic Model for Prediction Learning of Fluctuated Data Streams: Beyond Dichotomy between Probabilistic and Deterministic Models

DTIC Science & Technology

2014-11-04

learning by robots as well as video image understanding by accumulated learning of the exemplars are discussed. 15. SUBJECT TERMS Cognitive ...learning to predict perceptual streams or encountering events by acquiring internal models is indispensable for intelligent or cognitive systems because...various cognitive functions are based on this compentency including goal-directed planning, mental simulation and recognition of the current situation

Technology Support for Discussion Based Learning: From Computer Supported Collaborative Learning to the Future of Massive Open Online Courses

ERIC Educational Resources Information Center

Rosé, Carolyn Penstein; Ferschke, Oliver

2016-01-01

This article offers a vision for technology supported collaborative and discussion-based learning at scale. It begins with historical work in the area of tutorial dialogue systems. It traces the history of that area of the field of Artificial Intelligence in Education as it has made an impact on the field of Computer-Supported Collaborative…

Implementation Fest: The Last Decade

DTIC Science & Technology

2010-08-01

architectures New Learning Technologies  Simulations, games, and virtual world  Mobile systems  Performance support, S1000D tech manuals  Intelligent...Darwars Ambush (ECS) Gator 6 (Will Interactive) Games Today 22 VBS2 Enhanced Learning Environment using Creative Technology – Bilateral Negotiations...5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Advanced Decision Learning (ADL),1901 N. Beauregard Street Suite 600

National Intelligence University’s Role in Interagency Research: Recommendations from the Intelligence Community

DTIC Science & Technology

2013-01-01

outreach, and (4) social science and historical research/lessons learned . In some instances, the research entity fit into more than one category. We...Bureau of Intelligence and Research (INR) and the Analytic Outreach Initiative (AOI) at ODNI. Social science and historical research/lessons learned ...its coordination efforts, CSIR was interested in learning more about potential interagency research partners and how collaboration could be improved

Integrating Organizational Learning and Business Praxis: A Case for Intelligent Project Management.

ERIC Educational Resources Information Center

Cavaleri, Steven A.; Fearon, David S.

2000-01-01

Project management provides a natural home for organizational learning, freeing it from mechanical processes. Organizational learning plays a critical role in intelligent project management, which combines manageability, performance outcomes of knowledge management, and innovation. Learning should be integrated into an organization's core…

Toward an embedded training tool for Deep Space Network operations

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.; Sturdevant, Kathryn F.; Johnson, W. L.

1993-01-01

There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.

Event detection for car park entries by video-surveillance

NASA Astrophysics Data System (ADS)

Coquin, Didier; Tailland, Johan; Cintract, Michel

2007-10-01

Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting car park entries, using an adaptive background learning algorithm and two indicators representing activity and identity to overcome the difficulty of tracking objects.

SOAR: An Architecture for General Intelligence

DTIC Science & Technology

1987-12-01

these tasks, and (3) learn about all aspects of the tasks and its performance on them. Soar has existed since mid 1982 as an experimental software system...intelligence. Soar’s behavior has already been studied over a range of tasks and methods (Figure 1), which sample its intended range, though...in multiple small tasks: Generate and test, AND/OR search, hill climbing ( simple and steepest-ascent), means-ends analysis, operator subgoaling

Subgroup Discovery with User Interaction Data: An Empirically Guided Approach to Improving Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Poitras, Eric G.; Lajoie, Susanne P.; Doleck, Tenzin; Jarrell, Amanda

2016-01-01

Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…

What have we learned about intelligent transportation systems? Chapter 3, what have we learned about ITS? Arterial management

DOT National Transportation Integrated Search

1997-12-01

The two most important societal trends today are the aging baby boom and women's increased independence. This paper compares the travel profiles of women aged 40 to 49(early baby boomers) with women aged 75 and over and with men aged 75 and over (par...

Motivation and Performance in a Game-Based Intelligent Tutoring System

ERIC Educational Resources Information Center

Jackson, G. Tanner; McNamara, Danielle S.

2013-01-01

One strength of educational games stems from their potential to increase students' motivation and engagement during educational tasks. However, game features may also detract from principle learning goals and interfere with students' ability to master the target material. To assess the potential impact of game-based learning environments, in this…

How Should Intelligent Tutoring Systems Sequence Multiple Graphical Representations of Fractions? A Multi-Methods Study

ERIC Educational Resources Information Center

Rau, M. A.; Aleven, V.; Rummel, N.; Pardos, Z.

2014-01-01

Providing learners with multiple representations of learning content has been shown to enhance learning outcomes. When multiple representations are presented across consecutive problems, we have to decide in what sequence to present them. Prior research has demonstrated that interleaving "tasks types" (as opposed to blocking them) can…

Intelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams

ERIC Educational Resources Information Center

Hagge, Mathew; Amin-Naseri, Mostafa; Jackman, John; Guo, Enruo; Gilbert, Stephen B.; Starns, Gloria; Faidley, Leann

2017-01-01

Students learn when they connect new information to existing understanding or when they modify existing understanding to accept new information. Most current teaching methods focus on trying to get students to solve problems in a manner identical to that of an expert. This study investigates the effectiveness of assessing student understanding…

Cognitive-Operative Model of Intelligent Learning Systems Behavior

ERIC Educational Resources Information Center

Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; Mora-Torres, Martha; de Arriaga, Fernando; Escarela-Perez, Rafael

2010-01-01

In this paper behavior during the teaching-learning process is modeled by means of a fuzzy cognitive map. The elements used to model such behavior are part of a generic didactic model, which emphasizes the use of cognitive and operative strategies as part of the student-tutor interaction. Examples of possible initial scenarios for the…

More Efficient Learning on Web Courseware Systems?

ERIC Educational Resources Information Center

Zufic, Janko; Kalpic, Damir

2007-01-01

The article describes a research conducted on students at the University in Pula, by which was attempted to establish whether there is a relationship between exam success and a type of online teaching material from which a student learns. Students were subjected to psychological testing that measured factors of intelligence: verbal, non-verbal and…

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

ERIC Educational Resources Information Center

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

Learning Qualitative and Quantitative Reasoning in a Microworld for Elastic Impacts.

ERIC Educational Resources Information Center

Ploetzner, Rolf; And Others

1990-01-01

Discusses the artificial-intelligence-based microworld DiBi and MULEDS, a multilevel diagnosis system. Developed to adapt tutoring style to the individual learner. Explains that DiBi sets up a learning environment, and simulates elastic impacts as a subtopic of classical mechanics, and supporting reasoning on different levels of mental domain…

E-Learning Software for Improving Student's Music Performance Using Comparisons

ERIC Educational Resources Information Center

Delgado, M.; Fajardo, W.; Molina-Solana, M.

2013-01-01

In the last decades there have been several attempts to use computers in Music Education. New pedagogical trends encourage incorporating technology tools in the process of learning music. Between them, those systems based on Artificial Intelligence are the most promising ones, as they can derive new information from the inputs and visualize them…

Research on the transfer learning of the vehicle logo recognition

NASA Astrophysics Data System (ADS)

Zhao, Wei

2017-08-01

The Convolutional Neural Network of Deep Learning has been a huge success in the field of image intelligent transportation system can effectively solve the traffic safety, congestion, vehicle management and other problems of traffic in the city. Vehicle identification is a vital part of intelligent transportation, and the effective information in vehicles is of great significance to vehicle identification. With the traffic system on the vehicle identification technology requirements are getting higher and higher, the vehicle as an important type of vehicle information, because it should not be removed, difficult to change and other features for vehicle identification provides an important method. The current vehicle identification recognition (VLR) is mostly used to extract the characteristics of the method of classification, which for complex classification of its generalization ability to be some constraints, if the use of depth learning technology, you need a lot of training samples. In this paper, the method of convolution neural network based on transfer learning can solve this problem effectively, and it has important practical application value in the task of vehicle mark recognition.

Machine Learning. Part 1. A Historical and Methodological Analysis.

DTIC Science & Technology

1983-05-31

Machine learning has always been an integral part of artificial intelligence, and its methodology has evolved in concert with the major concerns of the field. In response to the difficulties of encoding ever-increasing volumes of knowledge in modern Al systems, many researchers have recently turned their attention to machine learning as a means to overcome the knowledge acquisition bottleneck. Part 1 of this paper presents a taxonomic analysis of machine learning organized primarily by learning strategies and secondarily by

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

NASA Astrophysics Data System (ADS)

Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

Assessing Student Learning through Multiple Intelligences.

ERIC Educational Resources Information Center

McClaskey, Janet

1995-01-01

Gives practical examples of multiple intelligences in the English classroom. Discusses Howard Gardner's "radicalism,""teaching" intelligence, teaching literature and multiple intelligences, and how a student developed strength in his own intelligences through poetry. (RS)

Understanding the Impact of a Half Day Learning Intervention on Emotional Intelligence Competencies: An Exploratory Study

ERIC Educational Resources Information Center

Carrick, Laurie Ann

2010-01-01

Empirical evidence has identified emotional intelligence competencies as part of the transformational leadership style. The development of emotional intelligence competencies has been reviewed in the context of a leadership development learning intervention encompassing the model of assessment, challenge and support. The exploratory study…

Multiple Intelligences and Language Learning Strategies: Investigating Possible Relations

ERIC Educational Resources Information Center

Akbari, Ramin; Hosseini, Kobra

2008-01-01

The present study was conducted to investigate the existence of any possible relationship between the use of language learning strategies and multiple intelligences' scores of foreign language learners of English. Ninety subjects participated in the study. To measure the participants' multiple intelligence scores, MIDAS, a commercially designed…

The Personal Intelligences: Promoting Social and Emotional Learning.

ERIC Educational Resources Information Center

Ellison, Launa

This book blends two of the multiple intelligences (intrapersonal and interpersonal) with current research on the brain and learning to create a new foundation for K-8 classrooms. It shares a teacher's classroom practices linking brain functions with the development of interpersonal and intrapersonal intelligence. Nine chapters include (1)…

Individual Differences in Learning from an Intelligent Discovery World: Smithtown.

ERIC Educational Resources Information Center

Shute, Valerie J.

"Smithtown" is an intelligent computer program designed to enhance an individual's scientific inquiry skills as well as to provide an environment for learning principles of basic microeconomics. It was hypothesized that intelligent computer instruction on applying effective interrogative skills (e.g., changing one variable at a time…

Fluid Intelligence and Discriminative Operant Learning of Reinforcement Contingencies in a Fixed Ratio 3 Schedule

ERIC Educational Resources Information Center

Lozano, J. H.; Hernandez, J. M.; Rubio, V. J.; Santacreu, J.

2011-01-01

Although intelligence has traditionally been identified as "the ability to learn" (Peterson, 1925), this relationship has been questioned in simple operant learning tasks (Spielberger, 1962). Nevertheless, recent pieces of research have demonstrated a strong and significant correlation between associative learning measures and intelligence…

Artificial intelligence in the service of system administrators

NASA Astrophysics Data System (ADS)

Haen, C.; Barra, V.; Bonaccorsi, E.; Neufeld, N.

2012-12-01

The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

Machine learning & artificial intelligence in the quantum domain: a review of recent progress

NASA Astrophysics Data System (ADS)

Dunjko, Vedran; Briegel, Hans J.

2018-07-01

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research—quantum information versus machine learning (ML) and artificial intelligence (AI)—have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our ‘big data’ world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement—exploring what ML/AI can do for quantum physics and vice versa—researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain.

Machine learning & artificial intelligence in the quantum domain: a review of recent progress.

PubMed

Dunjko, Vedran; Briegel, Hans J

2018-07-01

Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain.

Effect of promoting self-esteem by participatory learning process on emotional intelligence among early adolescents.

PubMed

Munsawaengsub, Chokchai; Yimklib, Somkid; Nanthamongkolchai, Sutham; Apinanthavech, Suporn

2009-12-01

To study the effect of promoting self-esteem by participatory learning program on emotional intelligence among early adolescents. The quasi-experimental study was conducted in grade 9 students from two schools in Bangbuathong district, Nonthaburi province. Each experimental and comparative group consisted of 34 students with the lowest score of emotional intelligence. The instruments were questionnaires, Program to Develop Emotional Intelligence and Handbook of Emotional Intelligence Development. The experimental group attended 8 participatory learning activities in 4 weeks to Develop Emotional Intelligence while the comparative group received the handbook for self study. Assessment the effectiveness of program was done by pre-test and post-test immediately and 4 weeks apart concerning the emotional intelligence. Implementation and evaluation was done during May 24-August 12, 2005. Data were analyzed by frequency, percentage, mean, standard deviation, Chi-square, independent sample t-test and paired sample t-test. Before program implementation, both groups had no statistical difference in mean score of emotional intelligence. After intervention, the experimental group had higher mean score of emotional intelligence both immediately and 4 weeks later with statistical significant (p = 0.001 and < 0.001). At 4 weeks after experiment, the mean score in experimental group was higher than the mean score at immediate after experiment with statistical significance (p < 0.001). The program to promote self-esteem by participatory learning process could enhance the emotional intelligence in early-adolescent. This program could be modified and implemented for early adolescent in the community.

Iranian EFL Learners' Emotional Intelligence, Learning Styles, Strategy Use, and Their L2 Achievement

ERIC Educational Resources Information Center

Afshar, Hassan Soodmand; Tofighi, Somayyeh; Hamazavi, Raouf

2016-01-01

The idea that language learning is facilitated or inhibited by a multitude of factors has prompted scholars in the field to investigate variables considered to be crucial in the process of second or foreign language learning. This study investigated relationships between emotional intelligence, learning style, language learning strategy use, and…

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

1971-01-01

A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

Indexing and retrieval of multimedia objects at different levels of granularity

NASA Astrophysics Data System (ADS)

Faudemay, Pascal; Durand, Gwenael; Seyrat, Claude; Tondre, Nicolas

1998-10-01

Intelligent access to multimedia databases for `naive user' should probably be based on queries formulation by `intelligent agents'. These agents should `understand' the semantics of the contents, learn user preferences and deliver to the user a subset of the source contents, for further navigation. The goal of such systems should be to enable `zero-command' access to the contents, while keeping the freedom of choice of the user. Such systems should interpret multimedia contents in terms of multiple audiovisual objects (from video to visual or audio object), and on actions and scenarios.

Distributed Control with Collective Intelligence

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Wheeler, Kevin R.; Tumer, Kagan

1998-01-01

We consider systems of interacting reinforcement learning (RL) algorithms that do not work at cross purposes , in that their collective behavior maximizes a global utility function. We call such systems COllective INtelligences (COINs). We present the theory of designing COINs. Then we present experiments validating that theory in the context of two distributed control problems: We show that COINs perform near-optimally in a difficult variant of Arthur's bar problem [Arthur] (and in particular avoid the tragedy of the commons for that problem), and we also illustrate optimal performance in the master-slave problem.

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Refining fuzzy logic controllers with machine learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1994-01-01

In this paper, we describe the GARIC (Generalized Approximate Reasoning-Based Intelligent Control) architecture, which learns from its past performance and modifies the labels in the fuzzy rules to improve performance. It uses fuzzy reinforcement learning which is a hybrid method of fuzzy logic and reinforcement learning. This technology can simplify and automate the application of fuzzy logic control to a variety of systems. GARIC has been applied in simulation studies of the Space Shuttle rendezvous and docking experiments. It has the potential of being applied in other aerospace systems as well as in consumer products such as appliances, cameras, and cars.

Text-to-audiovisual speech synthesizer for children with learning disabilities.

PubMed

Mendi, Engin; Bayrak, Coskun

2013-01-01

Learning disabilities affect the ability of children to learn, despite their having normal intelligence. Assistive tools can highly increase functional capabilities of children with learning disorders such as writing, reading, or listening. In this article, we describe a text-to-audiovisual synthesizer that can serve as an assistive tool for such children. The system automatically converts an input text to audiovisual speech, providing synchronization of the head, eye, and lip movements of the three-dimensional face model with appropriate facial expressions and word flow of the text. The proposed system can enhance speech perception and help children having learning deficits to improve their chances of success.

The Paradox of Expertise.

ERIC Educational Resources Information Center

Hankins, George.

1987-01-01

Describes the novice-to-expert model of human learning and compares it to the recent advances in the areas of artificial intelligence and expert systems. Discusses some of the characteristics of experts, proposing connections between them with expert systems and theories of left-right brain functions. (TW)

Analytic Hierarchy Process for Personalising Environmental Information

ERIC Educational Resources Information Center

Kabassi, Katerina

2014-01-01

This paper presents how a Geographical Information System (GIS) can be incorporated in an intelligent learning software system for environmental matters. The system is called ALGIS and incorporates the GIS in order to present effectively information about the physical and anthropogenic environment of Greece in a more interactive way. The system…

Application of Adaptive Decision Aiding Systems to Computer-Assisted Instruction. Final Report, January-December 1974.

ERIC Educational Resources Information Center

May, Donald M.; And Others

The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

An Intelligent Simulator for Telerobotics Training

ERIC Educational Resources Information Center

Belghith, K.; Nkambou, R.; Kabanza, F.; Hartman, L.

2012-01-01

Roman Tutor is a tutoring system that uses sophisticated domain knowledge to monitor the progress of students and advise them while they are learning how to operate a space telerobotic system. It is intended to help train operators of the Space Station Remote Manipulator System (SSRMS) including astronauts, operators involved in ground-based…

A New KE-Free Online ICALL System Featuring Error Contingent Feedback

ERIC Educational Resources Information Center

Tokuda, Naoyuki; Chen, Liang

2004-01-01

As a first step towards implementing a human language teacher, we have developed a new template-based on-line ICALL (intelligent computer assisted language learning) system capable of automatically diagnosing learners' free-format translated inputs and returning error contingent feedback. The system architecture we have adopted allows language…

SAMS--a systems architecture for developing intelligent health information systems.

PubMed

Yılmaz, Özgün; Erdur, Rıza Cenk; Türksever, Mustafa

2013-12-01

In this paper, SAMS, a novel health information system architecture for developing intelligent health information systems is proposed and also some strategies for developing such systems are discussed. The systems fulfilling this architecture will be able to store electronic health records of the patients using OWL ontologies, share patient records among different hospitals and provide physicians expertise to assist them in making decisions. The system is intelligent because it is rule-based, makes use of rule-based reasoning and has the ability to learn and evolve itself. The learning capability is provided by extracting rules from previously given decisions by the physicians and then adding the extracted rules to the system. The proposed system is novel and original in all of these aspects. As a case study, a system is implemented conforming to SAMS architecture for use by dentists in the dental domain. The use of the developed system is described with a scenario. For evaluation, the developed dental information system will be used and tried by a group of dentists. The development of this system proves the applicability of SAMS architecture. By getting decision support from a system derived from this architecture, the cognitive gap between experienced and inexperienced physicians can be compensated. Thus, patient satisfaction can be achieved, inexperienced physicians are supported in decision making and the personnel can improve their knowledge. A physician can diagnose a case, which he/she has never diagnosed before, using this system. With the help of this system, it will be possible to store general domain knowledge in this system and the personnel's need to medical guideline documents will be reduced.

An intelligent multi-media human-computer dialogue system

NASA Technical Reports Server (NTRS)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

Integrating Intelligent Systems Domain Knowledge Into the Earth Science Curricula

NASA Astrophysics Data System (ADS)

Güereque, M.; Pennington, D. D.; Pierce, S. A.

2017-12-01

High-volume heterogeneous datasets are becoming ubiquitous, migrating to center stage over the last ten years and transcending the boundaries of computationally intensive disciplines into the mainstream, becoming a fundamental part of every science discipline. Despite the fact that large datasets are now pervasive across industries and academic disciplines, the array of skills is generally absent from earth science programs. This has left the bulk of the student population without access to curricula that systematically teach appropriate intelligent-systems skills, creating a void for skill sets that should be universal given their need and marketability. While some guidance regarding appropriate computational thinking and pedagogy is appearing, there exist few examples where these have been specifically designed and tested within the earth science domain. Furthermore, best practices from learning science have not yet been widely tested for developing intelligent systems-thinking skills. This research developed and tested evidence based computational skill modules that target this deficit with the intention of informing the earth science community as it continues to incorporate intelligent systems techniques and reasoning into its research and classrooms.

Development and training of a learning expert system in an autonomous mobile robot via simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spelt, P.F.; Lyness, E.; DeSaussure, G.

1989-11-01

The Center for Engineering Systems Advanced Research (CESAR) conducts basic research in the area of intelligent machines. Recently at CESAR a learning expert system was created to operate on board an autonomous robot working at a process control panel. The authors discuss two-computer simulation system used to create, evaluate and train this learning system. The simulation system has a graphics display of the current status of the process being simulated, and the same program which does the simulating also drives the actual control panel. Simulation results were validated on the actual robot. The speed and safety values of using amore » computerized simulator to train a learning computer, and future uses of the simulation system, are discussed.« less

SCAILET: An intelligent assistant for satellite ground terminal operations

NASA Technical Reports Server (NTRS)

Shahidi, A. K.; Crapo, J. A.; Schlegelmilch, R. F.; Reinhart, R. C.; Petrik, E. J.; Walters, J. L.; Jones, R. E.

1993-01-01

NASA Lewis Research Center has applied artificial intelligence to an advanced ground terminal. This software application is being deployed as an experimenter interface to the link evaluation terminal (LET) and was named Space Communication Artificial Intelligence for the Link Evaluation Terminal (SCAILET). The high-burst-rate (HBR) LET provides 30-GHz-transmitting and 20-GHz-receiving, 220-Mbps capability for wide band communications technology experiments with the Advanced Communication Technology Satellite (ACTS). The HBR-LET terminal consists of seven major subsystems. A minicomputer controls and monitors these subsystems through an IEEE-488 or RS-232 protocol interface. Programming scripts (test procedures defined by design engineers) configure the HBR-LET and permit data acquisition. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. This discourages experimenters from utilizing the full capabilities of the HBR-LET system. An intelligent assistant module was developed as part of the SCAILET software. The intelligent assistant addresses critical experimenter needs by solving and resolving problems that are encountered during the configuring of the HBR-LET system. The intelligent assistant is a graphical user interface with an expert system running in the background. In order to further assist and familiarize an experimenter, an on-line hypertext documentation module was developed and included in the SCAILET software.

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

Learning by Reading for Robust Reasoning in Intelligent Agents

DTIC Science & Technology

2018-04-24

SUPPLEMENTARY NOTES 14. ABSTRACT Our hypotheses are that analogical processing plays multiple roles in enabling machines to learn by reading, and that...systems). Our overall hypotheses are that analogical processing plays multiple roles in learning by reading, and that qualitative representations provide...from reading this text? Narrative function can be seen as a kind of communication act, but the idea goes a bit beyond that. Communication acts are

The Application of Artificial Intelligence to Human Resource Development. A Case Study in the Development of a Rule-Based Expert System for Performance Analysis and Development Planning.

ERIC Educational Resources Information Center

Hummel, Thomas J.; Robinson, Judith A.

In 1984, the University of Minnesota's College of Education and Wilson Learning Corporation created the Alliance for Learning to support a variety of research projects focused on developing new areas of knowledge about adult learning and new technologies for delivering training and education. This paper describes an Alliance project exploring the…

Learning Effects of Interactive Whiteboard Pedagogy for Students in Taiwan from the Perspective of Multiple Intelligences

ERIC Educational Resources Information Center

Chen, Hong-Ren; Chiang, Chih-Hao; Lin, Wen-Shan

2013-01-01

With the rapid progress in information technology, interactive whiteboards have become IT-integrated in teaching activities. The theory of multiple intelligences argues that every person possesses multiple intelligences, emphasizing learners' cognitive richness and the possible role of these differences in enhanced learning. This study is the…

The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

ERIC Educational Resources Information Center

Hali, Nur Ihsan

2017-01-01

This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

Prerequisites for Emotional Intelligence Formation in Second Language Learning and Career Choice

ERIC Educational Resources Information Center

Baklashova, Tatiana A.; Galishnikova, Elena M.; Khafizova, Liliya A.

2016-01-01

The relevance of the topic is due to the enhancing role of emotional intelligence in second language learning. The article aims to substantiate that emotional intelligence (EI) strengthens training quality of future professionals, gives it an emotional color, and thereby increases a variety of intellectual skills. The leading methodical approaches…

Validating the Learning Disability Screening Questionnaire against the Weschler Adult Intelligence Scale, Fourth Edition

ERIC Educational Resources Information Center

McKenzie, Karen; Sharples, Phil; Murray, Aja L.

2015-01-01

The Learning Disability Screening Questionnaire (LDSQ), a brief screening tool for intellectual disability, was originally validated against the Weschler Adult Intelligence Scale, Third Edition (WAIS-III), which was superseded by the Weschler Adult Intelligence Scale, Fourth Edition (WAIS-IV) in the United Kingdom in 2010. This study examines the…

Ubiquitous and Ambient Intelligence Assisted Learning Environment Infrastructures Development--A Review

ERIC Educational Resources Information Center

Kanagarajan, Sujith; Ramakrishnan, Sivakumar

2018-01-01

Ubiquitous Learning Environment (ULE) has been becoming a mobile and sensor based technology equipped environment that suits the modern world education discipline requirements for the past few years. Ambient Intelligence (AmI) makes much smarter the ULE by the support of optimization and intelligent techniques. Various efforts have been so far…

Training Strategies for the Twenty-First Century: Using Recent Research on Learning To Enhance Training.

ERIC Educational Resources Information Center

Dwyer, Brian M.

2002-01-01

Discusses a new training model that takes into account the diversity of learners and the emotional, physical and social environmental conditions essential for lifelong learning. Considers how the brain learns and functions, brain-based learning, multiple intelligence, and emotional intelligence as well as personal reflection. (LRW)

Learning and Tuning of Fuzzy Rules

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1997-01-01

In this chapter, we review some of the current techniques for learning and tuning fuzzy rules. For clarity, we refer to the process of generating rules from data as the learning problem and distinguish it from tuning an already existing set of fuzzy rules. For learning, we touch on unsupervised learning techniques such as fuzzy c-means, fuzzy decision tree systems, fuzzy genetic algorithms, and linear fuzzy rules generation methods. For tuning, we discuss Jang's ANFIS architecture, Berenji-Khedkar's GARIC architecture and its extensions in GARIC-Q. We show that the hybrid techniques capable of learning and tuning fuzzy rules, such as CART-ANFIS, RNN-FLCS, and GARIC-RB, are desirable in development of a number of future intelligent systems.

Think Pair Share Using Realistic Mathematics Education Approach in Geometry Learning

NASA Astrophysics Data System (ADS)

Afthina, H.; Mardiyana; Pramudya, I.

2017-09-01

This research aims to determine the impact of mathematics learning applying Think Pair Share (TPS) using Realistic Mathematics Education (RME) viewed from mathematical-logical intelligence in geometry learning. Method that used in this research is quasi experimental research The result of this research shows that (1) mathematics achievement applying TPS using RME approach gives a better result than those applying direct learning model; (2) students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low one, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one; (3) there is no interaction between learning model and the level of students’ mathematical-logical intelligence in giving a mathematics achievement. The impact of this research is that TPS model using RME approach can be applied in mathematics learning so that students can learn more actively and understand the material more, and mathematics learning become more meaningful. On the other hand, internal factors of students must become a consideration toward the success of students’ mathematical achievement particularly in geometry material.

An intelligent assistant for physicians.

PubMed

Gavrilis, Dimitris; Georgoulas, George; Vasiloglou, Nikolaos; Nikolakopoulos, George

2016-08-01

This paper presents a software tool developed for assisting physicians during an examination process. The tool consists of a number of modules with the aim to make the examination process not only quicker but also fault proof moving from a simple electronic medical records management system towards an intelligent assistant for the physician. The intelligent component exploits users' inputs as well as well established standards to line up possible suggestions for filling in the examination report. As the physician continues using it, the tool keeps extracting new knowledge. The architecture of the tool is presented in brief while the intelligent component which builds upon the notion of multilabel learning is presented in more detail. Our preliminary results from a real test case indicate that the performance of the intelligent module can reach quite high performance without a large amount of data.

A Survey on Ambient Intelligence in Health Care

PubMed Central

Acampora, Giovanni; Cook, Diane J.; Rashidi, Parisa; Vasilakos, Athanasios V.

2013-01-01

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths. PMID:24431472

A Survey on Ambient Intelligence in Health Care.

PubMed

Acampora, Giovanni; Cook, Diane J; Rashidi, Parisa; Vasilakos, Athanasios V

2013-12-01

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

Public Health Intelligence: Learning From the Ebola Crisis

PubMed Central

Weber, David Jay

2015-01-01

Today’s public health crises, as exemplified by the Ebola outbreak, lead to dramatic calls to action that typically include improved electronic monitoring systems to better prepare for, and respond to, similar occurrences in the future. Even a preliminary public health informatics evaluation of the current Ebola crisis exposes the need for enhanced coordination and sharing of trustworthy public health intelligence. We call for a consumer-centric model of public health intelligence and the formation of a national center to guide public health intelligence gathering and synthesis. Sharing accurate and actionable information with government agencies, health care practitioners, policymakers, and, critically, the general public, will mark a shift from doing public health surveillance on people to doing public health surveillance for people. PMID:26180978

Making intelligent systems team players. A guide to developing intelligent monitoring systems

NASA Technical Reports Server (NTRS)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Intelligent process mapping through systematic improvement of heuristics

NASA Technical Reports Server (NTRS)

Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.

1992-01-01

The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.

Development of Intelligent Computer-Assisted Instruction Systems to Facilitate Reading Skills of Learning-Disabled Children

DTIC Science & Technology

1993-12-01

Unclassified/Unlimited 13. ABSTRACT ~Maximum 2W0 worr*J The purpose of this thesis is to develop a high-level model to create seli"adapting software which...Department of Computer Science ABSTRACT The purpose of this thesis is to develop a high-level model to create self-adapting software which teaches learning...stimulating and demanding. The power of the system model described herein is that it can vary as needed by the individual student. The system will

Artificial Intelligence in Cardiology.

PubMed

Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

2018-06-12

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Mathematical intelligence developed in math learning with classical backsound music of the classical era

NASA Astrophysics Data System (ADS)

Karlimah

2018-05-01

This study examines the application of classical music backsound in mathematics learning. The method used is quasi experimental design nonequivalent pretest-posttest control group in elementary school students in Tasikmalaya city, Indonesia. The results showed that classical music contributed significantly to the mathematical intelligence of elementary school students. The mathematical intelligence shown is in the cognitive ability ranging from the level of knowledge to evaluation. High level mathematical intelligence is shown by students in reading and writing integers with words and numbers. The low level of mathematical intelligence exists in projecting the story into a mathematical problem. The implication of this research is the use of classical music backsound on learning mathematics should pay attention to the level of difficulty of mathematics material being studied.

Design of Teacher Assistance Tools in an Exploratory Learning Environment for Algebraic Generalization

ERIC Educational Resources Information Center

Gutierrez-Santos, S.; Geraniou, E.; Pearce-Lazard, D.; Poulovassilis, A.

2012-01-01

The MiGen project is designing and developing an intelligent exploratory environment to support 11-14-year-old students in their learning of algebraic generalization. Deployed within the classroom, the system also provides tools to assist teachers in monitoring students' activities and progress. This paper describes the design of these Teacher…

Interdisciplinary Research at the Intersection of CALL, NLP, and SLA: Methodological Implications from an Input Enhancement Project

ERIC Educational Resources Information Center

Ziegler, Nicole; Meurers, Detmar; Rebuschat, Patrick; Ruiz, Simón; Moreno-Vega, José L.; Chinkina, Maria; Li, Wenjing; Grey, Sarah

2017-01-01

Despite the promise of research conducted at the intersection of computer-assisted language learning (CALL), natural language processing, and second language acquisition, few studies have explored the potential benefits of using intelligent CALL systems to deepen our understanding of the process and products of second language (L2) learning. The…

Conformal Predictions in Multimedia Pattern Recognition

ERIC Educational Resources Information Center

Nallure Balasubramanian, Vineeth

2010-01-01

The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

Community-Organizing Agent: An Artificial Intelligent System for Building Learning Communities among Large Numbers of Learners

ERIC Educational Resources Information Center

Yang, Fan; Wang, Minjuan; Shen, Ruimin; Han, Peng

2007-01-01

Web-based (or online) learning provides an unprecedented flexibility and convenience to both learners and instructors. However, large online classes relying on instructor-centered presentations could tend to isolate many learners. The size of these classes and the wide dispersion of the learners make it challenging for instructors to interact with…

Behavior and Learning Difficulties in Children of Normal Intelligence Born to Alcoholic Mothers.

ERIC Educational Resources Information Center

Shaywitz, Sally E.; And Others

1980-01-01

Children referred to the Learning Disorders Unit of the Yale-New Haven Hospital were evaluated for indications of prenatal exposure to ethanol. Our results suggest a continuum of teratogenic effects of ethanol on the central nervous system. Journal availability The C. V. Mosby Co., 11830 Westline Industrial Dr., St. Louis, MO 63141. (Author)

What have we learned about intelligent transportation systems? Chapter 6, What have we learned about ITS for commercial vehicle operations? Status, challenges, and benefits of CVISN level 1 deployment

DOT National Transportation Integrated Search

2006-01-01

This handbook provides guidance and recommended practices on managing and controlling traffic on ramps with freeway facilities. The use or application of the guidance and recommendations provided will in time serve to enhance the use and effectivenes...

Microfluidic Power Generation

DTIC Science & Technology

2008-03-28

It is designed to help patients with retinitus pigmentosa . The eye glasses and photoprocessor worn on the waist are used to train the retinal ...patient [5]. ............................................................. 3 Figure 1.3: The Learning Retinal Implant from Intelligent Medical Systems...implantable biosensors [4]. Examples of such advances include the AbioCor implantable replacement heart (Figure 1.2), Learning Retinal Implant (Figure 1.3

Intelligent Assistance for Teachers in Collaborative E-Learning Environments

ERIC Educational Resources Information Center

Casamayor, Agustin; Amandi, Analia; Campo, Marcelo

2009-01-01

Collaborative learning environments provide a set of tools for students acting in groups to interact and accomplish an assigned task. In this kind of systems, students are free to express and communicate with each other, which usually lead to collaboration and communication problems that may require the intervention of a teacher. In this article,…

Data Analysis Tools and Methods for Improving the Interaction Design in E-Learning

ERIC Educational Resources Information Center

Popescu, Paul Stefan

2015-01-01

In this digital era, learning from data gathered from different software systems may have a great impact on the quality of the interaction experience. There are two main directions that come to enhance this emerging research domain, Intelligent Data Analysis (IDA) and Human Computer Interaction (HCI). HCI specific research methodologies can be…

How to Schedule Multiple Graphical Representations? A Classroom Experiment with an Intelligent Tutoring System for Fractions

ERIC Educational Resources Information Center

Rau, M. A.; Aleven, V.; Rummel, N.

2011-01-01

Graphical representations (GRs) of the learning content are often used for instruction (Ainsworth, 2006). When used in learning technology, GRs can be especially useful since they allow for interactions across representations that are physically impossible, for instance by dragging and dropping symbolic statements into a chart that automatically…