Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

NASA Technical Reports Server (NTRS)

Broderick, Ron

1997-01-01

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

Artificial Intelligence: Applications in Education.

ERIC Educational Resources Information Center

Thorkildsen, Ron J.; And Others

1986-01-01

Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

Complexity, Heuristic, and Search Analysis for the Games of Crossings and Epaminondas

DTIC Science & Technology

2014-03-27

research in Artifical Intelligence (Section 2.1) and why games are studied (Section 2.2). Section 2.3 discusses how games are played and solved. An...5 2.1 Games in Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Game Study...Artificial Intelligence UCT Upper Confidence Bounds applied to Trees HUCT Heuristic Guided UCT LOA Lines of Action UCB Upper Confidence Bound RAVE Rapid

LISP on a Reduced-Instruction-Set-Processor,

DTIC Science & Technology

1986-01-01

Digital * Press, 1984. 19. Steele, G. L. Jr., and Sussman, G.J. LAMBDA : The Ultimate Imperative. Al Memo 353, MIT, Artificial ,, Inteligence Laboratory...procedure B is No 444, MIT Artificial Intelligence Laboratory, August, recursive, if procedure A can be reexecuted before the call 1977. returns. This...the programs Artificial Intelligence Programming. Lawrence Erlbaum use apply and eval, and of these three only frl uses eval Associates, Hillsdale, New

The role of artificial intelligence and expert systems in increasing STS operations productivity

NASA Technical Reports Server (NTRS)

Culbert, C.

1985-01-01

Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

Artificial Intelligence Applications in Special Education: How Feasible? Final Report.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Ferrara, Joseph M.

The research project investigated whether expert system tools have become sophisticated enough to be applied efficiently to problems in special education. (Expert systems are a development of artificial intelligence that combines the computer's capacity for storing specialized knowledge with a general set of rules intended to replicate the…

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science --Agent-based modeling --Applied mathematics --Artificial intelligence --Cloud computing management -Intelligence & counterterrorrism -Vulnerability assessment -Sensors & detectors Programs

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.

Artificial Neural Networks: A New Approach to Predicting Application Behavior.

ERIC Educational Resources Information Center

Gonzalez, Julie M. Byers; DesJardins, Stephen L.

2002-01-01

Applied the technique of artificial neural networks to predict which students were likely to apply to one research university. Compared the results to the traditional analysis tool, logistic regression modeling. Found that the addition of artificial intelligence models was a useful new tool for predicting student application behavior. (EV)

[Artificial intelligence--the knowledge base applied to nephrology].

PubMed

Sancipriano, G P

2005-01-01

The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

Implications of Artificial Intelligence for End User Use of Online Systems.

ERIC Educational Resources Information Center

Smith, Linda C.

1980-01-01

Reviewed are several studies which demonstrate how artificial intelligence techniques can be applied in the design of end user-oriented interfaces (which would eliminate the need for an intermediary) to existing online systems, as well as in the development of future generations of online systems intended for the end user. (Author/SW)

Automated Test Requirement Document Generation

DTIC Science & Technology

1987-11-01

DIAGNOSTICS BASED ON THE PRINCIPLES OF ARTIFICIAL INTELIGENCE ", 1984 International Test Conference, 01Oct84, (A3, 3, Cs D3, E2, G2, H2, 13, J6, K) 425...j0O GLOSSARY OF ACRONYMS 0 ABBREVIATION DEFINITION AFSATCOM Air Force Satellite Communication Al Artificial Intelligence ASIC Application Specific...In-Test Equipment (BITE) and AI ( Artificial Intelligence) - Expert Systems - need to be fully applied before a completely automated process can be

Estimation of urban runoff and water quality using remote sensing and artificial intelligence.

PubMed

Ha, S R; Park, S Y; Park, D H

2003-01-01

Water quality and quantity of runoff are strongly dependent on the landuse and landcover (LULC) criteria. In this study, we developed a more improved parameter estimation procedure for the environmental model using remote sensing (RS) and artificial intelligence (AI) techniques. Landsat TM multi-band (7bands) and Korea Multi-Purpose Satellite (KOMPSAT) panchromatic data were selected for input data processing. We employed two kinds of artificial intelligence techniques, RBF-NN (radial-basis-function neural network) and ANN (artificial neural network), to classify LULC of the study area. A bootstrap resampling method, a statistical technique, was employed to generate the confidence intervals and distribution of the unit load. SWMM was used to simulate the urban runoff and water quality and applied to the study watershed. The condition of urban flow and non-point contaminations was simulated with rainfall-runoff and measured water quality data. The estimated total runoff, peak time, and pollutant generation varied considerably according to the classification accuracy and percentile unit load applied. The proposed procedure would efficiently be applied to water quality and runoff simulation in a rapidly changing urban area.

Event classification and optimization methods using artificial intelligence and other relevant techniques: Sharing the experiences

NASA Astrophysics Data System (ADS)

Mohamed, Abdul Aziz; Hasan, Abu Bakar; Ghazali, Abu Bakar Mhd.

2017-01-01

Classification of large data into respected classes or groups could be carried out with the help of artificial intelligence (AI) tools readily available in the market. To get the optimum or best results, optimization tool could be applied on those data. Classification and optimization have been used by researchers throughout their works, and the outcomes were very encouraging indeed. Here, the authors are trying to share what they have experienced in three different areas of applied research.

Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

PubMed

Das, Nilakash; Topalovic, Marko; Janssens, Wim

2018-03-01

The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases. Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies. Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.

The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

PubMed

Collado-Mesa, Fernando; Alvarez, Edilberto; Arheart, Kris

2018-02-21

Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey was conducted among trainees and attending radiologists at a single residency program. An anonymous questionnaire was distributed. Comparisons of categorical data between groups (trainees and attending radiologists) were made using Pearson χ 2 analysis or an exact analysis when required. Comparisons were made using the Wilcoxon rank sum test when the data were not normally distributed. An α level of 0.05 was used. The overall response rate was 66% (69 of 104). Thirty-six percent of participants (n = 25) reported not having read a scientific medical article on the topic of artificial intelligence during the past 12 months. Twenty-nine percent of respondents (n = 12) reported using artificial intelligence tools during their daily work. Trainees were more likely to express doubts on whether they would have pursued diagnostic radiology as a career had they known of the potential impact artificial intelligence is predicted to have on the specialty (P = .0254) and were also more likely to plan to learn about the topic (P = .0401). Radiologists lack exposure to current scientific medical articles on artificial intelligence. Trainees are concerned by the implications artificial intelligence may have on their jobs and desire to learn about the topic. There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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.

Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

NASA Technical Reports Server (NTRS)

Swanson, David J.

1990-01-01

The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

Application of artifical intelligence principles to the analysis of "crazy" speech.

PubMed

Garfield, D A; Rapp, C

1994-04-01

Artificial intelligence computer simulation methods can be used to investigate psychotic or "crazy" speech. Here, symbolic reasoning algorithms establish semantic networks that schematize speech. These semantic networks consist of two main structures: case frames and object taxonomies. Node-based reasoning rules apply to object taxonomies and pathway-based reasoning rules apply to case frames. Normal listeners may recognize speech as "crazy talk" based on violations of node- and pathway-based reasoning rules. In this article, three separate segments of schizophrenic speech illustrate violations of these rules. This artificial intelligence approach is compared and contrasted with other neurolinguistic approaches and is discussed as a conceptual link between neurobiological and psychodynamic understandings of psychopathology.

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…

Utilization of artificial intelligence techniques for the Space Station power system

NASA Technical Reports Server (NTRS)

Evatt, Thomas C.; Gholdston, Edward W.

1988-01-01

Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

Artificial intelligence in a mission operations and satellite test environment

NASA Technical Reports Server (NTRS)

Busse, Carl

1988-01-01

A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

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.

Employing Textual and Facial Emotion Recognition to Design an Affective Tutoring System

ERIC Educational Resources Information Center

Lin, Hao-Chiang Koong; Wang, Cheng-Hung; Chao, Ching-Ju; Chien, Ming-Kuan

2012-01-01

Emotional expression in Artificial Intelligence has gained lots of attention in recent years, people applied its affective computing not only in enhancing and realizing the interaction between computers and human, it also makes computer more humane. In this study, emotional expressions were applied into intelligent tutoring system, where learners'…

The application and development of artificial intelligence in smart clothing

NASA Astrophysics Data System (ADS)

Wei, Xiong

2018-03-01

This paper mainly introduces the application of artificial intelligence in intelligent clothing. Starting from the development trend of artificial intelligence, analysis the prospects for development in smart clothing with artificial intelligence. Summarize the design key of artificial intelligence in smart clothing. Analysis the feasibility of artificial intelligence in smart clothing.

Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques.

PubMed

Ferreira, F J O; Crispim, V R; Silva, A X

2010-06-01

In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials. Copyright 2010 Elsevier Ltd. All rights reserved.

Spacecraft Health Automated Reasoning Prototype (SHARP): The fiscal year 1989 SHARP portability evaluations task for NASA Solar System Exploration Division's Voyager project

NASA Technical Reports Server (NTRS)

Atkinson, David J.; Doyle, Richard J.; James, Mark L.; Kaufman, Tim; Martin, R. Gaius

1990-01-01

A Spacecraft Health Automated Reasoning Prototype (SHARP) portability study is presented. Some specific progress is described on the portability studies, plans for technology transfer, and potential applications of SHARP and related artificial intelligence technology to telescience operations. The application of SHARP to Voyager telecommunications was a proof-of-capability demonstration of artificial intelligence as applied to the problem of real time monitoring functions in planetary mission operations. An overview of the design and functional description of the SHARP system is also presented as it was applied to Voyager.

Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

PubMed

Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

2015-06-01

This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. © The Author(s) 2013.

Intelligent detection of cracks in metallic surfaces using a waveguide sensor loaded with metamaterial elements.

PubMed

Ali, Abdulbaset; Hu, Bing; Ramahi, Omar

2015-05-15

This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classification accuracy rates.

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.

Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements

PubMed Central

Ali, Abdulbaset; Hu, Bing; Ramahi, Omar M.

2015-01-01

This work presents a real-life experiment implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impacts in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing the data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks, and the experimental results showed good crack classification accuracy rates. PMID:25988871

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

Forecasting daily lake levels using artificial intelligence approaches

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

2012-04-01

Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

Investigation of an artificial intelligence technology--Model trees. Novel applications for an immediate release tablet formulation database.

PubMed

Shao, Q; Rowe, R C; York, P

2007-06-01

This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.

A Workshop on the Integration of Numerical and Symbolic Computing Methods Held in Saratoga Springs, New York on July 9-11, 1990

DTIC Science & Technology

1991-04-01

SUMMARY OF COMPLETED PROJECT (for public use) The summary (about 200 words) must be self-contained and intellegible to a scientifically literate reader...dialogue among re- searchers in symbolic methods and numerical computation, and their appli- cations in certain disciplines of artificial intelligence...Lozano-Perez Purdue University Artificial Intelligence Laboratory West Lafayette, IN 47907 Massachusetts Institute of Technology (317) 494-6181 545

Airport Surface Traffic Automation Study.

DTIC Science & Technology

1988-05-09

the use of Artificial Intellignece * technology in enroute ATC can be applied directly to the surface control problem. 7.6 Development Approach The next...problems in airport surface control. If artificial intelligance provides useful results for airborne automation, the same techniques should prove useful

Artificial Intelligence for VHSIC Systems Design (AIVD) User Reference Manual

DTIC Science & Technology

1988-12-01

The goal of this program was to develop prototype tools which would use artificial intelligence techniques to extend the Architecture Design and Assessment (ADAS) software capabilities. These techniques were applied in a number of ways to increase the productivity of ADAS users. AIM will reduce the amount of time spent on tedious, negative, and error-prone steps. It will also provide f documentation that will assist users in varifying that the models they build are correct Finally, AIVD will help make ADAS models more reusable.

Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

NASA Astrophysics Data System (ADS)

Qiu, Feng; Dai, Guang; Zhang, Ying

According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

Outperforming Game Theoretic Play with Opponent Modeling in Two Player Dominoes

DTIC Science & Technology

2014-03-27

36 III. Methodology Introduction This chapter describes the methodology of how a dominoes artificial intelligence agent employs...Applying this concept to a partially observable game means that both players will have to model each other and have some intelligence of the board...

Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

NASA Astrophysics Data System (ADS)

Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

2014-06-01

This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

Syndrome Diagnosis: Human Intuition or Machine Intelligence?

PubMed Central

Braaten, Øivind; Friestad, Johannes

2008-01-01

The aim of this study was to investigate whether artificial intelligence methods can represent objective methods that are essential in syndrome diagnosis. Most syndromes have no external criterion standard of diagnosis. The predictive value of a clinical sign used in diagnosis is dependent on the prior probability of the syndrome diagnosis. Clinicians often misjudge the probabilities involved. Syndromology needs objective methods to ensure diagnostic consistency, and take prior probabilities into account. We applied two basic artificial intelligence methods to a database of machine-generated patients - a ‘vector method’ and a set method. As reference methods we ran an ID3 algorithm, a cluster analysis and a naive Bayes’ calculation on the same patient series. The overall diagnostic error rate for the the vector algorithm was 0.93%, and for the ID3 0.97%. For the clinical signs found by the set method, the predictive values varied between 0.71 and 1.0. The artificial intelligence methods that we used, proved simple, robust and powerful, and represent objective diagnostic methods. PMID:19415142

Syndrome diagnosis: human intuition or machine intelligence?

PubMed

Braaten, Oivind; Friestad, Johannes

2008-01-01

The aim of this study was to investigate whether artificial intelligence methods can represent objective methods that are essential in syndrome diagnosis. Most syndromes have no external criterion standard of diagnosis. The predictive value of a clinical sign used in diagnosis is dependent on the prior probability of the syndrome diagnosis. Clinicians often misjudge the probabilities involved. Syndromology needs objective methods to ensure diagnostic consistency, and take prior probabilities into account. We applied two basic artificial intelligence methods to a database of machine-generated patients - a 'vector method' and a set method. As reference methods we ran an ID3 algorithm, a cluster analysis and a naive Bayes' calculation on the same patient series. The overall diagnostic error rate for the the vector algorithm was 0.93%, and for the ID3 0.97%. For the clinical signs found by the set method, the predictive values varied between 0.71 and 1.0. The artificial intelligence methods that we used, proved simple, robust and powerful, and represent objective diagnostic methods.

Artificial intelligence in sports on the example of weight training.

PubMed

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key pointsArtificial intelligence is a promising field for sport-related analysis.Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements.Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates.

Artificial Intelligence in Sports on the Example of Weight Training

PubMed Central

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key points Artificial intelligence is a promising field for sport-related analysis. Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements. Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates. PMID:24149722

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Research activity has shifted from computer graphics and vision systems to the broader scope of applying concepts of artificial intelligence to robotics. Specifically, the research is directed toward developing Artificial Neural Networks, Expert Systems, and Laser Imaging Techniques for Autonomous Space Robots.

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background.

PubMed

Penco, Silvana; Buscema, Massimo; Patrosso, Maria Cristina; Marocchi, Alessandro; Grossi, Enzo

2008-05-30

Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg. This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.

Adaptive Educational Software by Applying Reinforcement Learning

ERIC Educational Resources Information Center

Bennane, Abdellah

2013-01-01

The introduction of the intelligence in teaching software is the object of this paper. In software elaboration process, one uses some learning techniques in order to adapt the teaching software to characteristics of student. Generally, one uses the artificial intelligence techniques like reinforcement learning, Bayesian network in order to adapt…

Artificial Intelligence and Information Retrieval.

ERIC Educational Resources Information Center

Teodorescu, Ioana

1987-01-01

Compares artificial intelligence and information retrieval paradigms for natural language understanding, reviews progress to date, and outlines the applicability of artificial intelligence to question answering systems. A list of principal artificial intelligence software for database front end systems is appended. (CLB)

Use of artificial intelligence to analyze clinical database reduces workload on surgical house staff.

PubMed

Grossi, E A; Steinberg, B M; LeBoutillier, M; Coppa, G F; Roses, D F

1994-08-01

The current quantity and diversity of hospital clinical, laboratory, and pharmacy records have resulted in a glut of information, which can be overwhelming to house staff. This study was performed to measure the impact of artificial intelligence analysis of such data on the junior surgical house staff's workload, time for direct patient care, and quality of life. A personal computer was interfaced with the hospital computerized patient data system. Artificial intelligence algorithms were applied to retrieve and condense laboratory values, microbiology reports, and medication orders. Unusual laboratory tests were reported without artificial intelligence filtering. A survey of 23 junior house staff showed a requirement for a total of 30.75 man-hours per day, an average of 184.5 minutes per service twice a day for five surgical services each with an average of 40.7 patients, to manually produce a report in contrast to a total of 3.4 man-hours, an average of 20.5 minutes on the same basis (88.9% reduction, p < 0.001), to computer generate and distribute a similarly useful report. Two thirds of the residents reported an increased ability to perform patient care. Current medical practice has created an explosion of information, which is a burden for surgical house staff. Artificial intelligence preprocessing of the hospital database information focuses attention, eliminates superfluous data, and significantly reduces surgical house staff clerical work, allowing more time for education, research, and patient care.

Design and Implementation of a Relational Database Management System for the AFIT Thesis Process.

DTIC Science & Technology

1985-09-01

AIRLIFT Gourdin 4. APPLIED MATHEMATICS Daneman Lee Na rga rsen ker 5. ARTIFICIAL INTELLEGENCE Gen et 6. CAPARILITY ASSESSMENT S Budde Talbott 31...05 ARTIFICIAL INTELLIGENCE 06 CAPABILITY ASSESSMENT 07 COMMUNIICATIONS 08 COMPUTER AIDED DESIGN 09 COMPUTER BASED TRAINING 10 COMPUTER SOFTWARE 11

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.

The application of artificial intelligence for the identification of the maceral groups and mineral components of coal

NASA Astrophysics Data System (ADS)

Mlynarczuk, Mariusz; Skiba, Marta

2017-06-01

The correct and consistent identification of the petrographic properties of coal is an important issue for researchers in the fields of mining and geology. As part of the study described in this paper, investigations concerning the application of artificial intelligence methods for the identification of the aforementioned characteristics were carried out. The methods in question were used to identify the maceral groups of coal, i.e. vitrinite, inertinite, and liptinite. Additionally, an attempt was made to identify some non-organic minerals. The analyses were performed using pattern recognition techniques (NN, kNN), as well as artificial neural network techniques (a multilayer perceptron - MLP). The classification process was carried out using microscopy images of polished sections of coals. A multidimensional feature space was defined, which made it possible to classify the discussed structures automatically, based on the methods of pattern recognition and algorithms of the artificial neural networks. Also, from the study we assessed the impact of the parameters for which the applied methods proved effective upon the final outcome of the classification procedure. The result of the analyses was a high percentage (over 97%) of correct classifications of maceral groups and mineral components. The paper discusses also an attempt to analyze particular macerals of the inertinite group. It was demonstrated that using artificial neural networks to this end makes it possible to classify the macerals properly in over 91% of cases. Thus, it was proved that artificial intelligence methods can be successfully applied for the identification of selected petrographic features of coal.

CREATIVE COMPUTATION.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , RECURSIVE FUNCTIONS), (*RECURSIVE FUNCTIONS, ARTIFICIAL INTELLIGENCE ), (*MATHEMATICAL LOGIC, ARTIFICIAL INTELLIGENCE ), METAMATHEMATICS, AUTOMATA, NUMBER THEORY, INFORMATION THEORY, COMBINATORIAL ANALYSIS

Artificial Intelligence and Its Importance in Education.

ERIC Educational Resources Information Center

Tilmann, Martha J.

Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

Northeast Artificial Intelligence Consortium (NAIC) Review of Technical Tasks. Volume 2, Part 2.

DTIC Science & Technology

1987-07-01

A-A19 774 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUN (MIC) 1/5 YVIEN OF TEOICR. T.. (U) NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM SYRACUSE MY J...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM (NAIC) *p,* ~ Review of Technical Tasks ,.. 12 PERSONAL AUTHOR(S) (See reverse) . P VI J.F. Allen, P.B. Berra...See reverse) /" I ABSTRACT (Coninue on ’.wrse if necessary and identify by block number) % .. *. -. ’ The Northeast Artificial Intelligence Consortium

Proceedings of the Air Force Forum for Intelligent Tutoring Systems

DTIC Science & Technology

1989-04-01

interface help the students find facts? I recently developed an expert system that is used at the JFK Airport to help workers assign incoming planes to...of their errors and to make comparisons with optimal solution paths. Chapters 2, and 5 BIP, BIP II: Basic Instructional Program BIP applied knowledge...OFFICE SYMBOL 7a NAME OF MONITORING ORGANIZATION Center for Applied Artificial (If applicable) Training Systems Division Intelligence 1 6. ADDRESS (City

Economic development evaluation based on science and patents

NASA Astrophysics Data System (ADS)

Jokanović, Bojana; Lalic, Bojan; Milovančević, Miloš; Simeunović, Nenad; Marković, Dusan

2017-09-01

Economic development could be achieved through many factors. Science and technology factors could influence economic development drastically. Therefore the main aim in this study was to apply computational intelligence methodology, artificial neural network approach, for economic development estimation based on different science and technology factors. Since economic analyzing could be very challenging task because of high nonlinearity, in this study was applied computational intelligence methodology, artificial neural network approach, to estimate the economic development based on different science and technology factors. As economic development measure, gross domestic product (GDP) was used. As the science and technology factors, patents in different field were used. It was found that the patents in electrical engineering field have the highest influence on the economic development or the GDP.

Artificial Intelligence.

ERIC Educational Resources Information Center

Information Technology Quarterly, 1985

1985-01-01

This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

Towards Computational Fronesis: Verifying Contextual Appropriateness of Emotions

ERIC Educational Resources Information Center

Ptaszynski, Michal; Dybala, Pawel; Mazur, Michal; Rzepka, Rafal; Araki, Kenji; Momouchi, Yoshio

2013-01-01

This paper presents research in Contextual Affect Analysis (CAA) for the need of future application in intelligent agents, such as conversational agents or artificial tutors. The authors propose a new term, Computational Fronesis (CF), to embrace the tasks included in CAA applied to development of conversational agents such as artificial tutors.…

Artificial Intelligence Project

DTIC Science & Technology

1990-01-01

Artifcial Intelligence Project at The University of Texas at Austin, University of Texas at Austin, Artificial Intelligence Laboratory AITR84-01. Novak...Texas at Austin, Artificial Intelligence Laboratory A187-52, April 1987. Novak, G. "GLISP: A Lisp-Based Programming System with Data Abstraction...of Texas at Austin, Artificial Intelligence Laboratory AITR85-14.) Rim, Hae-Chang, and Simmons, R. F. "Extracting Data Base Knowledge from Medical

Artificial Intelligence and Vocational Education: An Impending Confluence.

ERIC Educational Resources Information Center

Roth, Gene L.; McEwing, Richard A.

1986-01-01

Reports on the relatively new field of artificial intelligence and its relationship to vocational education. Compares human intelligence with artificial intelligence. Discusses expert systems, natural language technology, and current trends. Lists potential applications for vocational education. (CH)

Web Intelligence and Artificial Intelligence in Education

ERIC Educational Resources Information Center

Devedzic, Vladan

2004-01-01

This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

Artificial intelligence in medicine: humans need not apply?

PubMed

Diprose, William; Buist, Nicholas

2016-05-06

Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant.

Northeast Artificial Intelligence Consortium Annual Report. Volume 2. 1988 Discussing, Using, and Recognizing Plans (NLP)

DTIC Science & Technology

1989-10-01

Encontro Portugues de Inteligencia Artificial (EPIA), Oporto, Portugal, September 1985. [15] N. J. Nilsson. Principles Of Artificial Intelligence. Tioga...FI1 F COPY () RADC-TR-89-259, Vol II (of twelve) Interim Report October 1969 AD-A218 154 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL...7a. NAME OF MONITORING ORGANIZATION Northeast Artificial Of p0ilcabe) Intelligence Consortium (NAIC) Rome_____ Air___ Development____Center

Intelligent Technologies in Library and Information Service Applications. ASIST Monograph Series.

ERIC Educational Resources Information Center

Lancaster, F. W.; Warner, Amy

The objective of this study was to gain enough familiarity with developments in artificial intelligence (AI) and related technologies to be able to advise the information service community on what can be applied today and what one might reasonably expect to be applicable to library and information services in the near future. The emphasis is on…

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

Artificial Intelligence.

ERIC Educational Resources Information Center

Thornburg, David D.

1986-01-01

Overview of the artificial intelligence (AI) field provides a definition; discusses past research and areas of future research; describes the design, functions, and capabilities of expert systems and the "Turing Test" for machine intelligence; and lists additional sources for information on artificial intelligence. Languages of AI are…

Modeling rainfall-runoff process using soft computing techniques

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa

2013-02-01

Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987-1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods.

Prerequisites for Deriving Formal Specifications from Natural Language Requirements.

DTIC Science & Technology

1983-04-01

International Joint Conference on Artificial Intell1ence, American Association for Artificial Intelligence, Mento Park, CA, 1981, 385-387. Mann, William C...Centering". Proceedings of the Seventh International Joint Conference on Artificial Intelligence, American Association for Artificial Intelligence, Mento

Artificial Intelligence Applied to the Command, Control, Communications, and Intelligence of the U.S. Central Command.

DTIC Science & Technology

1983-06-06

Command, Control, Communications, and Intelligence presented by the Armed Forced Communications Electronics Association and the perusal of many ...A great deal was also learned from the knowledgeable and helpful USAWC faculty and SSI staff as well as the curriculum which provided many insights to...actually an _ umbrella-label covering many disciplines. Thus, after a definition of Al, descriptions of a selection of its subfields will follow to set the

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…

AIonAI: a humanitarian law of artificial intelligence and robotics.

PubMed

Ashrafian, Hutan

2015-02-01

The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

PubMed

Ashrafian, Hutan

2017-04-01

The potential for artificial intelligences and robotics in achieving the capacity of consciousness, sentience and rationality offers the prospect that these agents have minds. If so, then there may be a potential for these minds to become dysfunctional, or for artificial intelligences and robots to suffer from mental illness. The existence of artificially intelligent psychopathology can be interpreted through the philosophical perspectives of mental illness. This offers new insights into what it means to have either robot or human mental disorders, but may also offer a platform on which to examine the mechanisms of biological or artificially intelligent psychiatric disease. The possibility of mental illnesses occurring in artificially intelligent individuals necessitates the consideration that at some level, they may have achieved a mental capability of consciousness, sentience and rationality such that they can subsequently become dysfunctional. The deeper philosophical understanding of these conditions in mankind and artificial intelligences might therefore offer reciprocal insights into mental health and mechanisms that may lead to the prevention of mental dysfunction.

Deep into the Brain: Artificial Intelligence in Stroke Imaging

PubMed Central

Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

2017-01-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives. PMID:29037014

Deep into the Brain: Artificial Intelligence in Stroke Imaging.

PubMed

Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

2017-09-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.

University of Tennessee Center for Space Transportation and Applied Research (CSTAR)

NASA Astrophysics Data System (ADS)

1995-10-01

The Center for Space Transportation and Applied Research had projects with space applications in six major areas: laser materials processing, artificial intelligence/expert systems, space transportation, computational methods, chemical propulsion, and electric propulsion. The closeout status of all these projects is addressed.

University of Tennessee Center for Space Transportation and Applied Research (CSTAR)

NASA Technical Reports Server (NTRS)

1995-01-01

The Center for Space Transportation and Applied Research had projects with space applications in six major areas: laser materials processing, artificial intelligence/expert systems, space transportation, computational methods, chemical propulsion, and electric propulsion. The closeout status of all these projects is addressed.

Instructional Applications of Artificial Intelligence.

ERIC Educational Resources Information Center

Halff, Henry M.

1986-01-01

Surveys artificial intelligence and the development of computer-based tutors and speculates on the future of artificial intelligence in education. Includes discussion of the definitions of knowledge, expert systems (computer systems that solve tough technical problems), intelligent tutoring systems (ITS), and specific ITSs such as GUIDON, MYCIN,…

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.

Artificial Intelligence and Autonomy: Opportunities and Challenges

DTIC Science & Technology

2017-10-01

Cleared for Public Release Artificial Intelligence & Autonomy Opportunities and Challenges Andrew Ilachinski October 2017 Copyright © 2017 CNA... Artificial Intelligence & Autonomy Opportunities and 5a. CONTRACT NUMBER N00014-16-D-5003 Challenges 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0605154N...conducted by unmanned and increasingly autonomous weapon systems. This exploratory study considers the state-of-the-art of artificial intelligence (AI

Artificial Intelligence Information Sources for the Beginner and Expert

DTIC Science & Technology

1991-05-01

SUBPLEETAR TMS T bepbhdi" Artificial Intelligence ApplictionsforMlitar Expertis SystemsWilasbrVA 527Mrh 91 12a. DSCRIBTION C AIITY 6 STAEENRTY CTO SECb.T...DLSIFC ISTR BUMATION OC Apnclassified pu ncrlase; ituied inlsife unlimited. Artificial Intelligence Information Sources for the Beginner and Expert...mgivenfdsac.dia.mil UUCP: {...).osu-cisidsac!mgiven ABSTRACT A tremendous amount of information on artificial intelligence is available via different

The Outline of Personhood Law Regarding Artificial Intelligences and Emulated Human Entities

NASA Astrophysics Data System (ADS)

Muzyka, Kamil

2013-12-01

On the verge of technological breakthroughs, which define and revolutionize our understanding of intelligence, cognition, and personhood, especially when speaking of artificial intelligences and mind uploads, one must consider the legal implications of granting personhood rights to artificial intelligences or emulated human entities

Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

PubMed

Rajpara, S M; Botello, A P; Townend, J; Ormerod, A D

2009-09-01

Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high-quality population-based study.

Integrated IMA (Information Mission Areas) IC (Information Center) Guide

DTIC Science & Technology

1989-06-01

COMPUTER AIDED DESIGN / COMPUTER AIDED MANUFACTURE 8-8 8.3.7 LIQUID CRYSTAL DISPLAY PANELS 8-8 8.3.8 ARTIFICIAL INTELLIGENCE APPLIED TO VI 8-9 8.4...2 10.3.1 DESKTOP PUBLISHING 10-3 10.3.2 INTELLIGENT COPIERS 10-5 10.3.3 ELECTRONIC ALTERNATIVES TO PRINTED DOCUMENTS 10-5 10.3.4 ELECTRONIC FORMS...Optical Disk LCD Units Storage Image Scanners Graphics Forms Output Generation Copiers Devices Software Optical Disk Intelligent Storage Copiers Work Group

Artificial Intelligence for Pathologists Is Not Near--It Is Here: Description of a Prototype That Can Transform How We Practice Pathology Tomorrow.

PubMed

Ye, Jay J

2015-07-01

Pathologists' daily tasks consist of both the professional interpretation of slides and the secretarial tasks of translating these interpretations into final pathology reports, the latter of which is a time-consuming endeavor for most pathologists. To describe an artificial intelligence that performs secretarial tasks, designated as Secretary-Mimicking Artificial Intelligence (SMILE). The underling implementation of SMILE is a collection of computer programs that work in concert to "listen to" the voice commands and to "watch for" the changes of windows caused by slide bar code scanning; SMILE responds to these inputs by acting upon PowerPath Client windows (Sunquest Information Systems, Tucson, Arizona) and its Microsoft Word (Microsoft, Redmond, Washington) Add-In window, eventuating in the reports being typed and finalized. Secretary-Mimicking Artificial Intelligence also communicates relevant information to the pathologist via the computer speakers and message box on the screen. Secretary-Mimicking Artificial Intelligence performs many secretarial tasks intelligently and semiautonomously, with rapidity and consistency, thus enabling pathologists to focus on slide interpretation, which results in a marked increase in productivity, decrease in errors, and reduction of stress in daily practice. Secretary-Mimicking Artificial Intelligence undergoes encounter-based learning continually, resulting in a continuous improvement in its knowledge-based intelligence. Artificial intelligence for pathologists is both feasible and powerful. The future widespread use of artificial intelligence in our profession is certainly going to transform how we practice pathology.

Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

DTIC Science & Technology

1989-03-01

American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

Genetic algorithms in teaching artificial intelligence (automated generation of specific algebras)

NASA Astrophysics Data System (ADS)

Habiballa, Hashim; Jendryscik, Radek

2017-11-01

The problem of teaching essential Artificial Intelligence (AI) methods is an important task for an educator in the branch of soft-computing. The key focus is often given to proper understanding of the principle of AI methods in two essential points - why we use soft-computing methods at all and how we apply these methods to generate reasonable results in sensible time. We present one interesting problem solved in the non-educational research concerning automated generation of specific algebras in the huge search space. We emphasize above mentioned points as an educational case study of an interesting problem in automated generation of specific algebras.

Behavioral biometrics for verification and recognition of malicious software agents

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2008-04-01

Homeland security requires technologies capable of positive and reliable identification of humans for law enforcement, government, and commercial applications. As artificially intelligent agents improve in their abilities and become a part of our everyday life, the possibility of using such programs for undermining homeland security increases. Virtual assistants, shopping bots, and game playing programs are used daily by millions of people. We propose applying statistical behavior modeling techniques developed by us for recognition of humans to the identification and verification of intelligent and potentially malicious software agents. Our experimental results demonstrate feasibility of such methods for both artificial agent verification and even for recognition purposes.

Artificial intelligence applied to process signal analysis

NASA Technical Reports Server (NTRS)

Corsberg, Dan

1988-01-01

Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

Using Intelligent System Approaches for Simulation of Electricity Markets

NASA Astrophysics Data System (ADS)

Hamagami, Tomoki

Significances and approaches of applying intelligent systems to artificial electricity market is discussed. In recent years, with the moving into restructuring of electric system in Japan, the deregulation for the electric market is progressing. The most major change of the market is a founding of JEPX (Japan Electric Power eXchange.) which is expected to help lower power bills through effective use of surplus electricity. The electricity market designates exchange of electric power between electric power suppliers (supplier agents) themselves. In the market, the goal of each supplier agents is to maximize its revenue for the entire trading period, and shows complex behavior, which can model by a multiagent platform. Using the multiagent simulations which have been studied as “artificial market" helps to predict the spot prices, to plan investments, and to discuss the rules of market. Moreover, intelligent system approaches provide for constructing more reasonable policies of each agents. This article, first, makes a brief summary of the electricity market in Japan and the studies of artificial markets. Then, a survey of tipical studies of artificial electricity market is listed. Through these topics, the future vision is presented for the studies.

Artificial Intelligence and Computer Assisted Instruction. CITE Report No. 4.

ERIC Educational Resources Information Center

Elsom-Cook, Mark

The purpose of the paper is to outline some of the major ways in which artificial intelligence research and techniques can affect usage of computers in an educational environment. The role of artificial intelligence is defined, and the difference between Computer Aided Instruction (CAI) and Intelligent Computer Aided Instruction (ICAI) is…

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part C: Basic AI topics

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

Readily understandable overviews of search oriented problem solving, knowledge representation, and computational logic are provided. Mechanization, automation and artificial intelligence are discussed as well as how they interrelate.

A Primer for Problem Solving Using Artificial Intelligence.

ERIC Educational Resources Information Center

Schell, George P.

1988-01-01

Reviews the development of artificial intelligence systems and the mechanisms used, including knowledge representation, programing languages, and problem processing systems. Eleven books and 6 journals are listed as sources of information on artificial intelligence. (23 references) (CLB)

Applied Information Systems Research Program (AISRP) Workshop 3 meeting proceedings

NASA Technical Reports Server (NTRS)

1993-01-01

The third Workshop of the Applied Laboratory Systems Research Program (AISRP) met at the Univeristy of Colorado's Laboratory for Atmospheric and Space Physics in August of 1993. The presentations were organized into four sessions: Artificial Intelligence Techniques; Scientific Visualization; Data Management and Archiving; and Research and Technology.

Technical Assessment: Autonomy

DTIC Science & Technology

2015-02-01

and video games . If DoD develops CONOPS for lower- performance systems, there is an opportunity to leverage a large amount of private investment, as the...originally designed for the Xbox video game platform, it is now being used or developed for retail environments, operating rooms, and physical therapy...approaches that render artificial intelligence less susceptible to intelligent influence. One area worthy of consideration is applied game theory, which

Functional approximation using artificial neural networks in structural mechanics

NASA Technical Reports Server (NTRS)

Alam, Javed; Berke, Laszlo

1993-01-01

The artificial neural networks (ANN) methodology is an outgrowth of research in artificial intelligence. In this study, the feed-forward network model that was proposed by Rumelhart, Hinton, and Williams was applied to the mapping of functions that are encountered in structural mechanics problems. Several different network configurations were chosen to train the available data for problems in materials characterization and structural analysis of plates and shells. By using the recall process, the accuracy of these trained networks was assessed.

A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems

DTIC Science & Technology

1990-11-01

Intelligence Systems," in Distributed Artifcial Intelligence , vol. II, L. Gasser and M. Huhns (eds), Pitman, London, 1989, pp. 413-430. Shaw, M. Harrow, B...IDTIC FILE COPY A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems N Michael I. Shaw...SUBTITLE 5. FUNDING NUMBERS A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems 6

2017 Cybersecurity Workshop: Readouts from Working Groups - Video Text

Science.gov Websites

applicability of artificial intelligence to search for cybersecurity gaps in our existing SKATA networks. Second primarily renewable that all back each other up; that are all highly intelligent, artificial intelligence we have in cyber security, digital technologies, artificial intelligence. We think that that would

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

Statistical Software and Artificial Intelligence: A Watershed in Applications Programming.

ERIC Educational Resources Information Center

Pickett, John C.

1984-01-01

AUTOBJ and AUTOBOX are revolutionary software programs which contain the first application of artificial intelligence to statistical procedures used in analysis of time series data. The artificial intelligence included in the programs and program features are discussed. (JN)

Artificial intelligence in astronomy - a forecast.

NASA Astrophysics Data System (ADS)

Adorf, H. M.

Since several years artificial intelligence techniques are being actively used in astronomy, particularly within the Hubble Space Telescope project. This contribution reviews achievements, analyses some problems of using artificial intelligence in an astronomical environment, and projects current AI programming trends into the future.

Knowledge-based processing for aircraft flight control

NASA Technical Reports Server (NTRS)

Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul

1994-01-01

This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.

Potential application of artificial concepts to aerodynamic simulation

NASA Technical Reports Server (NTRS)

Kutler, P.; Mehta, U. B.; Andrews, A.

1984-01-01

The concept of artificial intelligence as it applies to computational fluid dynamics simulation is investigated. How expert systems can be adapted to speed the numerical aerodynamic simulation process is also examined. A proposed expert grid generation system is briefly described which, given flow parameters, configuration geometry, and simulation constraints, uses knowledge about the discretization process to determine grid point coordinates, computational surface information, and zonal interface parameters.

In Pursuit of Artificial Intelligence.

ERIC Educational Resources Information Center

Watstein, Sarah; Kesselman, Martin

1986-01-01

Defines artificial intelligence and reviews current research in natural language processing, expert systems, and robotics and sensory systems. Discussion covers current commercial applications of artificial intelligence and projections of uses and limitations in library technical and public services, e.g., in cataloging and online information and…

[Advances in the research of application of artificial intelligence in burn field].

PubMed

Li, H H; Bao, Z X; Liu, X B; Zhu, S H

2018-04-20

Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface, diagnose burn depth, guide fluid supply during shock stage, and predict prognosis, with high accuracy. With the development of technology, artificial intelligence can provide more accurate information for burn surgeons to make clinical diagnosis and treatment strategies.

Analysis and Implementation of Robust Grasping Behaviors

DTIC Science & Technology

1990-05-01

34 Technical Report 992, MIT Artificial Intelligence Laboratory, Cambridge, MA, May, 1987. 2. Brooks, R. A. "Achieving Artifci &l Intelligence Through...DTIu FILE COPY Technical Report 1237 ’Analysis and Implementation of NRobust Grasping Behaviors Camille Z. Chammas MIT Artificial Intelligence ...describes research conducted at the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the laboratory’s

An Approach to Object Recognition: Aligning Pictorial Descriptions.

DTIC Science & Technology

1986-12-01

PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

Computer Simulated Visual and Tactile Feedback as an Aid to Manipulator and Vehicle Control,

DTIC Science & Technology

1981-05-08

STATEMENT ........................ 8 Artificial Intellegence Versus Supervisory Control ....... 8 Computer Generation of Operator Feedback...operator. Artificial Intelligence Versus Supervisory Control The use of computers to aid human operators can be divided into two catagories: artificial ...operator. Artificial intelligence ( A. I. ) attempts to give the computer maximum intelligence and to replace all operator functions by the computer

Artificial Intelligence in Astronomy

NASA Astrophysics Data System (ADS)

Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

2010-12-01

From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

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…

Artificial Intelligence and Language Comprehension.

ERIC Educational Resources Information Center

National Inst. of Education (DHEW), Washington, DC. Basic Skills Group. Learning Div.

The three papers in this volume concerning artificial intelligence and language comprehension were commissioned by the National Institute of Education to further the understanding of the cognitive processes that enable people to comprehend what they read. The first paper, "Artificial Intelligence and Language Comprehension," by Terry Winograd,…

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

Architecture of a Message-Driven Processor,

DTIC Science & Technology

1987-11-01

Jon Kaplan, Paul Song, Brian Totty, and Scott Wills Artifcial Intelligence Laboratory -4 Laboratory for Computer Science Massachusetts Institute of...Information Dally, Chao, Chien, Hassoun, Horwat, Kaplan, Song, Totty & Wills: Artificial Intelligence i Laboratory and Laboratory for Computer Science, MIT...applied to a problem if we could are 36 bits long (32 data bits + 4 tag bits) and are used to hold efficiently run programs with a granularity of 5s

Intelligent reservoir operation system based on evolving artificial neural networks

NASA Astrophysics Data System (ADS)

Chaves, Paulo; Chang, Fi-John

2008-06-01

We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.

Rule based artificial intelligence expert system for determination of upper extremity impairment rating.

PubMed

Lim, I; Walkup, R K; Vannier, M W

1993-04-01

Quantitative evaluation of upper extremity impairment, a percentage rating most often determined using a rule based procedure, has been implemented on a personal computer using an artificial intelligence, rule-based expert system (AI system). In this study, the rules given in Chapter 3 of the AMA Guides to the Evaluation of Permanent Impairment (Third Edition) were used to develop such an AI system for the Apple Macintosh. The program applies the rules from the Guides in a consistent and systematic fashion. It is faster and less error-prone than the manual method, and the results have a higher degree of precision, since intermediate values are not truncated.

Artificial Intelligence In Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Vogel, Alison Andrews

1991-01-01

Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

Impact of multi-resolution analysis of artificial intelligence models inputs on multi-step ahead river flow forecasting

NASA Astrophysics Data System (ADS)

Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

2013-12-01

Discrete wavelet transform was applied to decomposed ANN and ANFIS inputs.Novel approach of WNF with subtractive clustering applied for flow forecasting.Forecasting was performed in 1-5 step ahead, using multi-variate inputs.Forecasting accuracy of peak values and longer lead-time significantly improved.

A Research Program on Artificial Intelligence in Process Engineering.

ERIC Educational Resources Information Center

Stephanopoulos, George

1986-01-01

Discusses the use of artificial intelligence systems in process engineering. Describes a new program at the Massachusetts Institute of Technology which attempts to advance process engineering through technological advances in the areas of artificial intelligence and computers. Identifies the program's hardware facilities, software support,…

An Artificial Intelligence Approach for Gears Diagnostics in AUVs

PubMed Central

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-01-01

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

PubMed

Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

2016-04-12

In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

Demonstrating artificial intelligence for space systems - Integration and project management issues

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Difilippo, Denise M.

1990-01-01

As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

Dynamical Systems and Motion Vision.

DTIC Science & Technology

1988-04-01

TASK Artificial Inteligence Laboratory AREA I WORK UNIT NUMBERS 545 Technology Square . Cambridge, MA 02139 C\\ II. CONTROLLING OFFICE NAME ANO0 ADDRESS...INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I.Memo No. 1037 April, 1988 Dynamical Systems and Motion Vision Joachim Heel Abstract: In this... Artificial Intelligence L3 Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory’s [1 Artificial Intelligence Research is

Northeast Artificial Intelligence Consortium (NAIC). Volume 2. Discussing, Using, and Recognizing Plans

DTIC Science & Technology

1990-12-01

knowledge and meta-reasoning. In Proceedings of EP14-85 ("Encontro Portugues de Inteligencia Artificial "), pages 138-154, Oporto, Portugal, 1985. [19] N, J...See reverse) 7. PERFORMING ORGANIZATION NAME(S) AND ADORESS(ES) 8. PERFORMING ORGANIZATION Northeast Artificial Intelligence...ABSTRACTM-2.,-- The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and

Artificial Intelligence Study (AIS).

DTIC Science & Technology

1987-02-01

ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

Expertise, Task Complexity, and Artificial Intelligence: A Conceptual Framework.

ERIC Educational Resources Information Center

Buckland, Michael K.; Florian, Doris

1991-01-01

Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…

Partial Bibliography of Work on Expert Systems,

DTIC Science & Technology

1982-12-01

Bibliography: AAAI American Association for Artificial Intelligence ACM Association for Computing Machinery AFIPS American Federation of Information...Processing Societies ECAI European Conference on Artificial Intelligence IEEE Institute for Electrical and Electronic Engineers IFIPS International...Federation of Information Processing Societies IJCAI International Joint Conferences on Artificial Intelligence SIGPLAN ACM Special Interest Group on

AI applications to conceptual aircraft design

NASA Technical Reports Server (NTRS)

Chalfan, Kathryn M.

1990-01-01

This paper presents in viewgraph form several applications of artificial intelligence (AI) to the conceptual design of aircraft, including: an access manager for automated data management, AI techniques applied to optimization, and virtual reality for scientific visualization of the design prototype.

A Microworld Approach to the Formalization of Musical Knowledge.

ERIC Educational Resources Information Center

Honing, Henkjan

1993-01-01

Discusses the importance of applying computational modeling and artificial intelligence techniques to music cognition and computer music research. Recommends three uses of microworlds to trim computational theories to their bare minimum, allowing for better and easier comparison. (CFR)

The Case for Artificial Intelligence in Medicine

PubMed Central

Reggia, James A.

1983-01-01

Current artificial intelligence (AI) technology can be viewed as producing “systematic artifacts” onto which we project an interpretation of intelligent behavior. One major benefit this technology could bring to medicine is help with handling the tremendous and growing volume of medical knowledge. The reader is led to a vision of the medical library of tomorrow, an interactive, artificially intelligent knowledge source that is fully and directly integrated with daily patient care.

Naval Computer-Based Instruction: Cost, Implementation and Effectiveness Issues.

DTIC Science & Technology

1988-03-01

logical follow on to MITIPAC and are an attempt to use some artificial intelligence (AI) techniques with computer-based training. A good intelligent ...principles of steam plant operation and maintenance. Steamer was written in LISP on a LISP machine in an attempt to use artificial intelligence . "What... Artificial Intelligence and Speech Technology", Electronic Learning, September 1987. Montague, William. E., code 5, Navy Personnel Research and

Actors: A Model of Concurrent Computation in Distributed Systems.

DTIC Science & Technology

1985-06-01

Artificial Intelligence Labora- tory of the Massachusetts Institute of Technology. Support for the labora- tory’s aritificial intelligence research is...RD-A157 917 ACTORS: A MODEL OF CONCURRENT COMPUTATION IN 1/3- DISTRIBUTED SY𔃿TEMS(U) MASSACHUSETTS INST OF TECH CRMBRIDGE ARTIFICIAL INTELLIGENCE ...Computation In Distributed Systems Gui A. Aghai MIT Artificial Intelligence Laboratory Thsdocument ha. been cipp-oved I= pblicrelease and sale; itsI

The use of artificially intelligent agents with bounded rationality in the study of economic markets

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

Rajan, V.; Slagle, J.R.

The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

What Is Artificial Intelligence Anyway?

ERIC Educational Resources Information Center

Kurzweil, Raymond

1985-01-01

Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

Nuclear propulsion control and health monitoring

NASA Technical Reports Server (NTRS)

Walter, P. B.; Edwards, R. M.

1993-01-01

An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.

Nuclear propulsion control and health monitoring

NASA Astrophysics Data System (ADS)

Walter, P. B.; Edwards, R. M.

1993-11-01

An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Visiting Scholars Program

DTIC Science & Technology

2016-09-01

other associated grants. 15. SUBJECT TERMS SUNY Poly, STEM, Artificial Intelligence , Command and Control 16. SECURITY CLASSIFICATION OF: 17...neuromorphic system has the potential to be widely used in a high-efficiency artificial intelligence system. Simulation results have indicated that the...novel multiresolution fusion and advanced fusion performance evaluation tool for an Artificial Intelligence based natural language annotation engine for

The Joint Tactical Aerial Resupply Vehicle Impact on Sustainment Operations

DTIC Science & Technology

2017-06-09

Artificial Intelligence , Sustainment Operations, Rifle Company, Autonomous Aerial Resupply, Joint Tactical Autonomous Aerial Resupply System 16...Integrations and Development System AI Artificial Intelligence ARCIC Army Capabilities Integration Center ARDEC Armament Research, Development and...semi- autonomous systems, and fully autonomous systems. Autonomy of machines depends on sophisticated software, including Artificial Intelligence

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…

The importance of motivation and emotion for explaining human cognition.

PubMed

Güss, C Dominik; Dörner, Dietrich

2017-01-01

Lake et al. discuss building blocks of human intelligence that are quite different from those of artificial intelligence. We argue that a theory of human intelligence has to incorporate human motivations and emotions. The interaction of motivation, emotion, and cognition is the real strength of human intelligence and distinguishes it from artificial intelligence.

Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

DTIC Science & Technology

1989-10-01

Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

The 1990 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1990-01-01

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Educational Technology: Integration?

ERIC Educational Resources Information Center

Christensen, Dean L.; Tennyson, Robert D.

This paper presents a perspective of the current state of technology-assisted instruction integrating computer language, artificial intelligence (AI), and a review of cognitive science applied to instruction. The following topics are briefly discussed: (1) the language of instructional technology, i.e., programming languages, including authoring…

Artificial Intelligence Applications to High-Technology Training.

ERIC Educational Resources Information Center

Dede, Christopher

1987-01-01

Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

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.

Application Of The CSRL Language To The Design Of Diagnostic Expert Systems: The Moodis Experience, A Preliminary Report

NASA Astrophysics Data System (ADS)

Bravos, Angelo; Hill, Howard; Choca, James; Bresolin, Linda B.; Bresolin, Michael J.

1986-03-01

Computer technology is rapidly becoming an inseparable part of many health science specialties. Recently, a new area of computer technology, namely Artificial Intelligence, has been applied toward assisting the medical experts in their diagnostic and therapeutic decision making process. MOODIS is an experimental diagnostic expert system which assists Psychiatry specialists in diagnosing human Mood Disorders, better known as Affective Disorders. Its diagnostic methodology is patterned after MDX, a diagnostic expert system developed at LAIR (Laboratory for Artificial Intelligence Research) of Ohio State University. MOODIS is implemented in CSRL (Conceptual Structures Representation Language) also developed at LAIR. This paper describes MOODIS in terms of conceptualization and requirements, and discusses why the MDX approach and CSRL were chosen.

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.

Artificial intelligence and synthetic biology: A tri-temporal contribution.

PubMed

Bianchini, Francesco

2016-10-01

Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Protecting Networks Via Automated Defense of Cyber Systems

DTIC Science & Technology

2016-09-01

autonomics, and artificial intelligence . Our conclusion is that automation is the future of cyber defense, and that advances are being made in each of...SUBJECT TERMS Internet of Things, autonomics, sensors, artificial intelligence , cyber defense, active cyber defense, automated indicator sharing...called Automated Defense of Cyber Systems, built upon three core technological components: sensors, autonomics, and artificial intelligence . Our

Finding Edges and Lines in Images.

DTIC Science & Technology

1983-06-01

34 UNCLASSI FlED , SECURITY CLASSIFICATION OF THIS PAGE ("osen Data Entered) READ INSTRUCTIONSREPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM I. REPORT...PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA&WORKUNITNUMBERS 545 Technology Square...in the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory’s artificial intelligence research

Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

DTIC Science & Technology

1986-10-01

rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

Planning and Scheduling of Software Manufacturing Projects

DTIC Science & Technology

1991-03-01

based on the previous results in social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing...planning and scheduling, and the traditional approaches to planning in artificial intelligence, and extends the techniques that have been developed by them...social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing planning and scheduling, and the

Real Rules of Inference

DTIC Science & Technology

1986-01-01

the AAAI Workshop on Uncertainty and Probability in Artificial Intelligence , 1985. [McC771 McCarthy, J. "Epistemological Problems of Aritificial ...NUMBER OF PAGES Artificial Intelligence , Data Fusion, Inference, Probability, 30 Philosophy, Inheritance Hierachies, Default Reasoning ia.PRCECODE I...prominent philosophers Glymour and Thomason even applaud the uninhibited steps: Artificial Intelligence has done us the service not only of reminding us

Current Uses of Artificial Intelligence in Special Education. Abstract XI: Research & Resources on Special Education.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

Summarized are two reports of a federally funded project on the use of artificial intelligence in special education. The first report, "Artificial Intelligence Applications in Special Education: How Feasible?," by Alan Hofmeister and Joseph Ferrara, provides information on the development and evaluation of a series of prototype systems in special…

Cultural Modelling: Literature review

DTIC Science & Technology

2006-09-01

of mood and/or emotions. Our review did show some evidence that artificial intelligence research has tended to depict human decision making as...pp. 72-79). The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB). Halfill, T., Sundstrom, E., Nielsen, T. M...M. & Thagard, P. (2005). Changing personalities: Towards realistic virtual characters. Journal of Experimental & Theoretical Artificial Intelligence

"It's Going to Kill Us!" and Other Myths about the Future of Artificial Intelligence

ERIC Educational Resources Information Center

Atkinson, Robert D.

2016-01-01

Given the promise that artificial intelligence (AI) holds for economic growth and societal advancement, it is critical that policymakers not only avoid retarding the progress of AI innovation, but also actively support its further development and use. This report provides a primer on artificial intelligence and debunks five prevailing myths that,…

Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

ERIC Educational Resources Information Center

Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

2010-01-01

Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

ERIC Educational Resources Information Center

Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

2010-01-01

This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

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.

Intelligent Diagnosis of Degradation State under Corrosion

NASA Astrophysics Data System (ADS)

Isoc, Dorin; Ignat-Coman, Aurelian; Joldiş, Adrian

2008-06-01

The work presents an inter- and multi-disciplinary research where the diagnosis is treated by using the artificial intelligence means and the application the degradation state of buildings and urban power networks. A possible model of degradation process caused by the corrosion and the technical achievement manner is given. The notions of micro- and macro-modeling and model granularity are introduced and applied. For resulting model the specification of intelligent processing of information and further the knowledge for suggested model are prepared. As concluding remarks the results are analysed and interpreted and a generalized approach is suggested and argued.

ESD/MITRE Software Acquisition Symposium Proceedings; an ESD/Industry Dialogue held in Bedford, Massachusetts on May 6-7, 1986

DTIC Science & Technology

1986-05-07

Cycle? Moderator: Christine M. Anderson Dennis D. Doe Manager of Engineering Software and Artificial Intelligence Boeing Aerospace Company In... intelligence systems development pro- cess affect the life cycle? Artificial intelligence developers seem to be the last haven for people who don’t...of Engineering Software and Artificial Intelligence at the Boeing Aerospace Company. In this capacity, Mr. Doe is the focal point for software

Knowledge Based Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle.

DTIC Science & Technology

1988-04-13

Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle Mark S. Fox, Nizwer Husain, Malcolm...McRoberts and Y.V.Reddy CMU-RI-TR-88-5 Intelligent Systems Laboratory The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania D T T 13...years of research in the application of Artificial Intelligence to Simulation. Our focus has been in two areas: the use of Al knowledge representation

Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding.

DTIC Science & Technology

1983-09-01

AD-Ali33 592 ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF POTENTIAL 1/1 APPLICATIONS TO TRAININ..(U) DENVER RESEARCH INST CO JRICHARDSON SEP 83 AFHRL-TP...83-28 b ’ 3 - 4. TITLE (aied Suhkie) 5. TYPE OF REPORT & PERIOD COVERED ARTIFICIAL INTEL11GENCE: AN ANALYSIS OF Interim POTENTIAL APPLICATIONS TO...8217 sde if neceseamy end ides*f by black naumber) artificial intelligence military research * computer-aided diagnosis performance tests computer

AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

EPA Science Inventory

A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

Construction Grammar in ICALL

ERIC Educational Resources Information Center

Schulze, Mathias; Penner, Nikolai

2008-01-01

The choice of grammatical framework in ICALL--the branch of CALL that applies artificial intelligence techniques--has important implications for both research and development. Matthews (1993) argued for one "that potentially meshes with SLA (second language acquisition)" (p. 5) and sketches three criteria that facilitate the crucial…

Role and interest of new technologies in data processing for space control centers

NASA Astrophysics Data System (ADS)

Denier, Jean-Paul; Caspar, Raoul; Borillo, Mario; Soubie, Jean-Luc

1990-10-01

The ways in which a multidisplinary approach will improve space control centers is discussed. Electronic documentation, ergonomics of human computer interfaces, natural language, intelligent tutoring systems and artificial intelligence systems are considered and applied in the study of the Hermes flight control center. It is concluded that such technologies are best integrated into a classical operational environment rather than taking a revolutionary approach which would involve a global modification of the system.

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.

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

A Challenge to Watson

ERIC Educational Resources Information Center

Detterman, Douglas K.

2011-01-01

Watson's Jeopardy victory raises the question of the similarity of artificial intelligence and human intelligence. Those of us who study human intelligence issue a challenge to the artificial intelligence community. We will construct a unique battery of tests for any computer that would provide an actual IQ score for the computer. This is the same…

The image recognition based on neural network and Bayesian decision

NASA Astrophysics Data System (ADS)

Wang, Chugege

2018-04-01

The artificial neural network began in 1940, which is an important part of artificial intelligence. At present, it has become a hot topic in the fields of neuroscience, computer science, brain science, mathematics, and psychology. Thomas Bayes firstly reported the Bayesian theory in 1763. After the development in the twentieth century, it has been widespread in all areas of statistics. In recent years, due to the solution of the problem of high-dimensional integral calculation, Bayesian Statistics has been improved theoretically, which solved many problems that cannot be solved by classical statistics and is also applied to the interdisciplinary fields. In this paper, the related concepts and principles of the artificial neural network are introduced. It also summarizes the basic content and principle of Bayesian Statistics, and combines the artificial neural network technology and Bayesian decision theory and implement them in all aspects of image recognition, such as enhanced face detection method based on neural network and Bayesian decision, as well as the image classification based on the Bayesian decision. It can be seen that the combination of artificial intelligence and statistical algorithms has always been the hot research topic.

Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1990-01-01

The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

Research Needs for Artificial Intelligence Applications in Support of C3 (Command, Control, and Communication).

DTIC Science & Technology

1984-12-01

system. The reconstruction process is Simply data fusion after allA data are in. After reconstruction, artifcial intelligence (Al) techniques may be...14. CATE OF fhPM~TVW MWtvt Ogv It PAWE COMN Interim __100 -_ TO December 1984 24 MILD ON" s-o Artificial intelligence Command control Data fusion...RD-Ai5O 867 RESEARCH NEEDS FOR ARTIFICIAL INTELLIGENCE APPLICATIONS i/i IN SUPPORT OF C3 (..(U) NAVAL OCEAN SVSTEIIS CENTER SAN DIEGO CA R R DILLARD

A Cyber Situational Awareness Model for Network Administrators

DTIC Science & Technology

2017-03-01

environments, the Internet of Things, artificial intelligence , and so on. As users’ data requirements grow more complex, they demand information...security of systems of interest. Further, artificial intelligence is a powerful concept in information technology. Therefore, new research should...look into how to use artificial intelligence to develop CSA. Human interaction with cyber systems is not making networks and their components safer

The 1994 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Hostetter, Carl F. (Editor)

1994-01-01

This publication comprises the papers presented at the 1994 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/GSFC, Greenbelt, Maryland, on 10-12 May 1994. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

Artificial Intelligence and Its Potential as an Aid to Vocational Training and Education.

ERIC Educational Resources Information Center

Aleksander, I.; And Others

This document contains a series of papers which attempt to de-mystify the subject of artificial intelligence and to show how some countries in the European Community (EC) are approaching the promotion of development and application of artificial intelligence systems that can be used as an aid in vocational training programs, as well as to…

The Classification, Detection and Handling of Imperfect Theory Problems.

DTIC Science & Technology

1987-04-20

Explanation-Based Learning: Failure-Driven Schema Refinement." Proceedings of the Third IEEE Conference on Artificial Intelligence Applications . Orlando...A. Rajamoney. Gerald F. DeJong Artificial Intelligence Research Group " . Coordinated Science Laboratory " University of Illinois at Urbana-Champaign...Urbana. IL 61801 . April 1987 ABSTRACT This paper also appears in the Proceedings of the Tenth International Conference on Artificial Intelligence

Interdisciplinary Study on Artificial Intelligence.

DTIC Science & Technology

1983-07-01

systems, uiophysics of information processing, cognitive science, and traditional artificial intelligence. The objective behi d this objective was to...information processing, cognitive science, and traditional * artificial intelligence. The objective behind this objective was to provide a vehicle for reviewing...Another departure from ’classical’ neurodynamics must be sought in the strong coupling between the micro and macroscopic scales. No other physical mechanism

The 1993 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Hostetter, Carl F. (Editor)

1993-01-01

This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

Organisational Structure and Information Technology (IT): Exploring the Implications of IT for Future Military Structures

DTIC Science & Technology

2006-07-01

4 Abbreviations AI Artificial Intelligence AM Artificial Memory CAD Computer Aided...memory (AM), artificial intelligence (AI), and embedded knowledge systems it is possible to expand the “effective span of competence” of...Technology J Joint J2 Joint Intelligence J3 Joint Operations NATO North Atlantic Treaty Organisation NCW Network Centric Warfare NHS National Health

Patient behavior and the benefits of artificial intelligence: the perils of "dangerous" literacy and illusory patient empowerment.

PubMed

Schulz, Peter J; Nakamoto, Kent

2013-08-01

Artificial intelligence can provide important support of patient health. However, limits to realized benefits can arise as patients assume an active role in their health decisions. Distinguishing the concepts of health literacy and patient empowerment, we analyze conditions that bias patient use of the Internet and limit access to and impact of artificial intelligence. Improving health literacy in the face of the Internet requires significant guidance. Patients must be directed toward the appropriate tools and also provided with key background knowledge enabling them to use the tools and capitalize on the artificial intelligence technology. Benefits of tools employing artificial intelligence to promote health cannot be realized without recognizing and addressing the patients' desires, expectations, and limitations that impact their Internet behavior. In order to benefit from artificial intelligence, patients need a substantial level of background knowledge and skill in information use-i.e., health literacy. It is critical that health professionals respond to patient search for information on the Internet, first by guiding their search to relevant, authoritative, and responsive sources, and second by educating patients about how to interpret the information they are likely to encounter. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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…

STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

Artificial intelligence: A joint narrative on potential use in pediatric stem and immune cell therapies and regenerative medicine.

PubMed

Sniecinski, Irena; Seghatchian, Jerard

2018-05-09

Artificial Intelligence (AI) reflects the intelligence exhibited by machines and software. It is a highly desirable academic field of many current fields of studies. Leading AI researchers describe the field as "the study and design of intelligent agents". McCarthy invented this term in 1955 and defined it as "the science and engineering of making intelligent machines". The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. In fact the multidisplinary AI field is considered to be rather interdisciplinary covering numerous number of sciences and professions, including computer science, psychology, linguistics, philosophy and neurosciences. The field was founded on the claim that a central intellectual property of humans, intelligence-the sapience of Homo Sapiens "can be so precisely described that a machine can be made to simulate it". This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. Artificial Intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. The goal of this narrative is to review the potential use of AI approaches and their integration into pediatric cellular therapies and regenerative medicine. Emphasis is placed on recognition and application of AI techniques in the development of predictive models for personalized treatments with engineered stem cells, immune cells and regenerated tissues in adults and children. These intelligent machines could dissect the whole genome and isolate the immune particularities of individual patient's disease in a matter of minutes and create the treatment that is customized to patient's genetic specificity and immune system capability. AI techniques could be used for optimization of clinical trials of innovative stem cell and gene therapies in pediatric patients by precise planning of treatments, predicting clinical outcomes, simplifying recruitment and retention of patients, learning from input data and applying to new data, thus lowering their complexity and costs. Complementing human intelligence with machine intelligence could have an exponentially high impact on continual progress in many fields of pediatrics. However how long before we could see the real impact still remains the big question. The most pertinent question that remains to be answered therefore, is can AI effectively and accurately predict properties of newer DDR strategies? The goal of this article is to review the use of AI method for cellular therapy and regenerative medicine and emphasize its potential to further the progress in these fields of medicine. Copyright © 2018. Published by Elsevier Ltd.

Importance of nonverbal expression to the emergence of emotive artificial intelligence systems

NASA Astrophysics Data System (ADS)

Pioggia, Giovanni; Hanson, David; Dinelli, Serena; Di Francesco, Fabio; Francesconi, R.; De Rossi, Danilo

2002-07-01

The nonverbal expression of the emotions, especially in the human face, has rapidly become an area of intense interest in computer science and robotics. Exploring the emotions as a link between external events and behavioural responses, artificial intelligence designers and psychologists are approaching a theoretical understanding of foundational principles which will be key to the physical embodiment of artificial intelligence. In fact, it has been well demonstrated that many important aspects of intelligence are grounded in intimate communication with the physical world- so-called embodied intelligence . It follows naturally, then, that recent advances in emotive artificial intelligence show clear and undeniable broadening in the capacities of biologically-inspired robots to survive and thrive in a social environment. The means by which AI may express its foundling emotions are clearly integral to such capacities. In effect: powerful facial expressions are critical to the development of intelligent, sociable robots. Following discussion the importance of the nonverbal expression of emotions in humans and robots, this paper describes methods used in robotically emulating nonverbal expressions using human-like robotic faces. Furthermore, it describes the potentially revolutionary impact of electroactive polymer (EAP) actuators as artificial muscles for such robotic devices.

Speech Recognition for A Digital Video Library.

ERIC Educational Resources Information Center

Witbrock, Michael J.; Hauptmann, Alexander G.

1998-01-01

Production of the meta-data supporting the Informedia Digital Video Library interface is automated using techniques derived from artificial intelligence research. Speech recognition and natural-language processing, information retrieval, and image analysis are applied to produce an interface that helps users locate information and navigate more…

Artificial Intelligence in Precision Cardiovascular Medicine.

PubMed

Krittanawong, Chayakrit; Zhang, HongJu; Wang, Zhen; Aydar, Mehmet; Kitai, Takeshi

2017-05-30

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Artificial Intelligence in Medical Practice: The Question to the Answer?

PubMed

Miller, D Douglas; Brown, Eric W

2018-02-01

Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. Copyright © 2018 Elsevier Inc. All rights reserved.

A human performance modelling approach to intelligent decision support systems

NASA Technical Reports Server (NTRS)

Mccoy, Michael S.; Boys, Randy M.

1987-01-01

Manned space operations require that the many automated subsystems of a space platform be controllable by a limited number of personnel. To minimize the interaction required of these operators, artificial intelligence techniques may be applied to embed a human performance model within the automated, or semi-automated, systems, thereby allowing the derivation of operator intent. A similar application has previously been proposed in the domain of fighter piloting, where the demand for pilot intent derivation is primarily a function of limited time and high workload rather than limited operators. The derivation and propagation of pilot intent is presented as it might be applied to some programs.

Circumscribing Circumscription. A Guide to Relevance and Incompleteness,

DTIC Science & Technology

1985-10-01

other rules of conjecture, to account for resource limitations. P "- h’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo...of conjecture, to account for resource limitations. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts...Institute of Technology. Support for the laboratory’s artificial intelligence research is provided in part by the Advanced Research Projects Agency

Why the United States Must Adopt Lethal Autonomous Weapon Systems

DTIC Science & Technology

2017-05-25

2017. http://www.designboom.com/ technology /designboom-tech-predictions-robotics-12-26- 2016/. Egan, Matt. "Robots Write Thousands Of News Stories A...views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture sees artificial intelligence as an economic savior...Army, 37 pages. The East and West have differing views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture

Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

ERIC Educational Resources Information Center

Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.

2014-01-01

In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…

THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

DTIC Science & Technology

COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

PubMed

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

2012-11-21

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

2012-11-01

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

NASA Astrophysics Data System (ADS)

Chung, K. K.; Do, D. Q.

2010-09-01

In order to model relationships between chemical structures and biological effects in quantitative structure-activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data.

Artificial-intelligence-based optimization of the management of snow removal assets and resources.

DOT National Transportation Integrated Search

2002-10-01

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

Basic Research in Artificial Intelligence and Foundations of Programming

DTIC Science & Technology

1980-05-01

and Their Decision Problems, Proceedings Seventh ACM Symposium on Principles of Programming Languages, Las Vegas (Jan. 1980), pp. 62-67. 5. Z. Manna and...Semantics, Comunicaciones Tecnicas (in Spanish). Blue Series: monographs. Center 1 17. Nevatia, R., T.O. Binford; Structured for Research in Applied

(Some) Computer Futures: Mainframes.

ERIC Educational Resources Information Center

Joseph, Earl C.

Possible futures for the world of mainframe computers can be forecast through studies identifying forces of change and their impact on current trends. Some new prospects for the future have been generated by advances in information technology; for example, recent United States successes in applied artificial intelligence (AI) have created new…

Artificial intelligence in robot control systems

NASA Astrophysics Data System (ADS)

Korikov, A.

2018-05-01

This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

A Progress Report on Artificial Intelligence: Hospital Applications and a Review of the Artificial Intelligence Marketplace

PubMed Central

Brenkus, Lawrence M.

1984-01-01

Artificial intelligence applications are finally beginning to move from the university research laboratory into commercial use. Before the end of the century, this new computer technology will have profound effects on our work, economy, and lives. At present, relatively few products have appeared in the hospital, but we can anticipate significant product offerings in instrumentation and affecting hospital administration within 5 years.

A Spoken English Recognition Expert System.

DTIC Science & Technology

1983-09-01

Davidson. "Representation of Knowledge," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A. Felgenbaum. DTIC document number AD...Regents of the University of CalTorni, 1981. 9. Gardner, Anne. "Search," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A...Felgenbaum, DTIC document number AD A074078, 1979. 10. Gardner, Anne,et al. "Natural Language Understanding," Handbook of Artificial Intelligence, edited

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Strategic Computing. New-Generation Computing Technology: A Strategic Plan for Its Development and Application to Critical Problems in Defense

DTIC Science & Technology

1983-10-28

Computing. By seizing an opportunity to leverage recent advances in artificial intelligence, computer science, and microelectronics, the Agency plans...occurred in many separated areas of artificial intelligence, computer science, and microelectronics. Advances in "expert system" technology now...and expert knowledge o Advances in Artificial Intelligence: Mechanization of speech recognition, vision, and natural language understanding. o

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

NASA Technical Reports Server (NTRS)

Hostetter, Carl F. (Editor)

1995-01-01

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

Defense Information Systems Program Automated CORDIVEM Design Requirements,

DTIC Science & Technology

1984-02-28

for the Soviet military organization and equipment. Dr. John Spagnuolo incorporated artificial intelligence techniques in the discussion of functional...4-44 4.1.2.18.2 Artificial Intelligence ...... ........ 4-49 4.1.2.18.3 Types of A.I ................. 4-51 4.1.2.19 General Planning Requirements...described later. Further, some subprocesses may need one of the various techniques associated with the broad field of Artificial Intelligence (A.I.) in

[The application and development of artificial intelligence in medical diagnosis systems].

PubMed

Chen, Zhencheng; Jiang, Yong; Xu, Mingyu; Wang, Hongyan; Jiang, Dazong

2002-09-01

This paper has reviewed the development of artificial intelligence in medical practice and medical diagnostic expert systems, and has summarized the application of artificial neural network. It explains that a source of difficulty in medical diagnostic system is the co-existence of multiple diseases--the potentially inter-related diseases. However, the difficulty of image expert systems is inherent in high-level vision. And it increases the complexity of expert system in medical image. At last, the prospect for the development of artificial intelligence in medical image expert systems is made.

Application of decentralized cooperative problem solving in dynamic flexible scheduling

NASA Astrophysics Data System (ADS)

Guan, Zai-Lin; Lei, Ming; Wu, Bo; Wu, Ya; Yang, Shuzi

1995-08-01

The object of this study is to discuss an intelligent solution to the problem of task-allocation in shop floor scheduling. For this purpose, the technique of distributed artificial intelligence (DAI) is applied. Intelligent agents (IAs) are used to realize decentralized cooperation, and negotiation is realized by using message passing based on the contract net model. Multiple agents, such as manager agents, workcell agents, and workstation agents, make game-like decisions based on multiple criteria evaluations. This procedure of decentralized cooperative problem solving makes local scheduling possible. And by integrating such multiple local schedules, dynamic flexible scheduling for the whole shop floor production can be realized.

Artificial Intelligence.

ERIC Educational Resources Information Center

Wash, Darrel Patrick

1989-01-01

Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

On DSS Implementation in the Dynamic Model of the Digital Oil field

NASA Astrophysics Data System (ADS)

Korovin, Iakov S.; Khisamutdinov, Maksim V.; Kalyaev, Anatoly I.

2018-02-01

Decision support systems (DSS), especially based on the artificial intelligence (AI) techniques are been widely applied in different domains nowadays. In the paper we depict an approach of implementing DSS in to Digital Oil Field (DOF) dynamic model structure in order to reduce the human factor influence, considering the automation of all production processes to be the DOF model clue element. As the basic tool of data handling we propose the hybrid application on artificial neural networks and evolutional algorithms.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Northeast Artificial Intelligence Consortium Annual Report - 1988 Parallel Vision. Volume 9

DTIC Science & Technology

1989-10-01

supports the Northeast Aritificial Intelligence Consortium (NAIC). Volume 9 Parallel Vision Report submitted by Christopher M. Brown Randal C. Nelson...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT - 1988 Parallel Vision Syracuse University Christopher M. Brown and Randal C. Nelson...Technical Director Directorate of Intelligence & Reconnaissance FOR THE COMMANDER: IGOR G. PLONISCH Directorate of Plans & Programs If your address has

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

Artificial intelligence in nanotechnology.

PubMed

Sacha, G M; Varona, P

2013-11-15

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

Artificial intelligence in nanotechnology

NASA Astrophysics Data System (ADS)

Sacha, G. M.; Varona, P.

2013-11-01

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

Collaboration and Computer-Assisted Acquisition of a Second Language.

ERIC Educational Resources Information Center

Renie, Delphine; Chanier, Thierry

1995-01-01

Discusses how collaborative learning (CL) can be used in a computer-assisted learning (CAL) environment for language learning, reviewing research in the fields of applied linguistics, educational psychology, and artificial intelligence. An application of CL and CAL in the learning of French as a Second Language, focusing on interrogative…

Applying AI to the Writer's Learning Environment.

ERIC Educational Resources Information Center

Houlette, Forrest

1991-01-01

Discussion of current applications of artificial intelligence (AI) to writing focuses on how to represent knowledge of the writing process in a way that links procedural knowledge to other types of knowledge. A model is proposed that integrates the subtasks of writing into the process of writing itself. (15 references) (LRW)

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

Computer Intelligence: Unlimited and Untapped.

ERIC Educational Resources Information Center

Staples, Betsy

1983-01-01

Herbert Simon (Nobel prize-winning economist/professor) expresses his views on human and artificial intelligence, problem solving, inventing concepts, and the future. Includes comments on expert systems, state of the art in artificial intelligence, robotics, and "Bacon," a computer program that finds scientific laws hidden in raw data.…

Expert Systems and Special Education.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Ferrara, Joseph M.

The application of artificial intelligence to the problems of education is examined. One of the most promising areas in artificial intelligence is expert systems technology which engages the user in a problem-solving diaglogue. Some of the characteristics that make expert systems "intelligent" are identified and exemplified. The rise of…

Artificial Intelligence Applications for Education: Promise, ...Promises.

ERIC Educational Resources Information Center

Adams, Dennis M.; Hamm, Mary

1988-01-01

Surveys the current status of artificial intelligence (AI) technology. Discusses intelligent tutoring systems, robotics, and applications for educators. Likens the status of AI at present to that of aviation in the very early 1900s. States that educators need to be involved in future debates concerning AI. (CW)

Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

PubMed

Cascianelli, Silvia; Scialpi, Michele; Amici, Serena; Forini, Nevio; Minestrini, Matteo; Fravolini, Mario Luca; Sinzinger, Helmut; Schillaci, Orazio; Palumbo, Barbara

2017-01-01

Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

[Algorithms of artificial neural networks--practical application in medical science].

PubMed

Stefaniak, Bogusław; Cholewiński, Witold; Tarkowska, Anna

2005-12-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer applications of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. This paper presents practical aspects of scientific application of ANN in medicine using widely available algorithms. Several main steps of analysis with ANN were discussed starting from material selection and dividing it into groups, to the quality assessment of obtained results at the end. The most frequent, typical reasons for errors as well as the comparison of ANN method to the modeling by regression analysis were also described.

Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 4. Part A. Hierarchical Region-Based Approach to Automatic Photointerpretation. Part B. Application of AI Techniques to Image Segmentation and Region Identification

DTIC Science & Technology

1988-01-01

MONITORING ORGANIZATION Northeast Artificial (If applicaole)nelincCostum(AcRome Air Development Center (COCU) Inteligence Consortium (NAIC)I 6c. ADDRESS...f, Offell RADC-TR-88-1 1, Vol IV (of eight) Interim Technical ReportS June 1988 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1986...13441-5700 EMENT NO NO NO ACCESSION NO62702F 5 8 71 " " over) I 58 27 13 " ൓ TITLE (Include Security Classification) NORTHEAST ARTIFICIAL INTELLIGENCE

Artificial Neural Networks and Instructional Technology.

ERIC Educational Resources Information Center

Carlson, Patricia A.

1991-01-01

Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

Artificial Intelligence and Educational Technology: A Natural Synergy. Extended Abstract.

ERIC Educational Resources Information Center

McCalla, Gordon I.

Educational technology and artificial intelligence (AI) are natural partners in the development of environments to support human learning. Designing systems with the characteristics of a rich learning environment is the long term goal of research in intelligent tutoring systems (ITS). Building these characteristics into a system is extremely…

Applications of Artificial Intelligence in Education--A Personal View.

ERIC Educational Resources Information Center

Richer, Mark H.

1985-01-01

Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search

DTIC Science & Technology

1976-07-01

Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Len-t APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED (A...570 AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Lenat ABSTRACT A program, called "AM", is...While AM’s " approach " to empirical research may be used in other scientific domains, the main limitation (reliance on hindsight) will probably recur

A Computer-Aided Instruction Program for Teaching the TOPS20-MM Facility on the DDN (Defense Data Network)

DTIC Science & Technology

1988-06-01

Continue on reverse if necessary and identify by block number) FIELD GROUP SUB-GROUP Computer Assisted Instruction; Artificial Intelligence 194...while he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been...he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been used

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

PubMed Central

Contreras, Ivan

2018-01-01

Background Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. Objective The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. Methods A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. Results We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. Conclusions We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients’ quality of life. PMID:29848472

Center for Artificial Intelligence

DTIC Science & Technology

1992-03-14

builder’s intelligent assistant. The basic approach of IGOR is to integrate the complementary strategies of exploratory and confirmatory data analysis...Recovery: A Model and Experiments," in Proceedings of the Ninth National Conference on Artifcial Intelligence , Anaheim, CA, July 1991, pp. 801-808. Howe...Lehnert University of Massachusetts, Amherst, MAJ (413) 545-1322 Lessei•:s.umass.edu Title: Center for Artificial Intelligence Contract #: N00014-86-K

Fluid Flow Technology that Measures Up

NASA Technical Reports Server (NTRS)

2004-01-01

From 1994 to 1996, NASA s Marshall Space Flight Center conducted a Center Director's Discretionary Fund research effort to apply artificial intelligence technologies to the health management of plant equipment and space propulsion systems. Through this effort, NASA established a business relationship with Quality Monitoring and Control (QMC), of Kingwood, Texas, to provide hardware modeling and artificial intelligence tools. Very detailed and accurate Space Shuttle Main Engine (SSME) analysis and algorithms were jointly created, which identified several missing, critical instrumentation needs for adequately evaluating the engine health status. One of the missing instruments was a liquid oxygen (LOX) flow measurement. This instrument was missing since the original SSME included a LOX turbine flow meter that failed during a ground test, resulting in considerable damage for NASA. New balanced flow meter technology addresses this need with robust, safe, and accurate flow metering hardware.

STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

NASA Technical Reports Server (NTRS)

Rogers, James L.; Feyock, Stefan; Sobieszczanski-Sobieski, Jaroslaw

1988-01-01

The purpose of this research effort is to investigate the benefits that might be derived from applying artificial intelligence tools in the area of conceptual design. Therefore, the emphasis is on the artificial intelligence aspects of conceptual design rather than structural and optimization aspects. A prototype knowledge-based system, called STRUTEX, was developed to initially configure a structure to support point loads in two dimensions. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user by integrating a knowledge base interface and inference engine, a data base interface, and graphics while keeping the knowledge base and data base files separate. The system writes a file which can be input into a structural synthesis system, which combines structural analysis and optimization.

Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

NASA Astrophysics Data System (ADS)

Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

1994-09-01

A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

Application of Artificial Intelligence for Bridge Deterioration Model.

PubMed

Chen, Zhang; Wu, Yangyang; Li, Li; Sun, Lijun

2015-01-01

The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

Application of Artificial Intelligence for Bridge Deterioration Model

PubMed Central

Chen, Zhang; Wu, Yangyang; Sun, Lijun

2015-01-01

The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention. PMID:26601121

Estimation of mechanical properties of nanomaterials using artificial intelligence methods

NASA Astrophysics Data System (ADS)

Vijayaraghavan, V.; Garg, A.; Wong, C. H.; Tai, K.

2014-09-01

Computational modeling tools such as molecular dynamics (MD), ab initio, finite element modeling or continuum mechanics models have been extensively applied to study the properties of carbon nanotubes (CNTs) based on given input variables such as temperature, geometry and defects. Artificial intelligence techniques can be used to further complement the application of numerical methods in characterizing the properties of CNTs. In this paper, we have introduced the application of multi-gene genetic programming (MGGP) and support vector regression to formulate the mathematical relationship between the compressive strength of CNTs and input variables such as temperature and diameter. The predictions of compressive strength of CNTs made by these models are compared to those generated using MD simulations. The results indicate that MGGP method can be deployed as a powerful method for predicting the compressive strength of the carbon nanotubes.

A self-taught artificial agent for multi-physics computational model personalization.

PubMed

Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin

2016-12-01

Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.

Integrated human-machine intelligence in space systems.

PubMed

Boy, G A

1992-07-01

This paper presents an artificial intelligence approach to integrated human-machine intelligence in space systems. It discusses the motivations for Intelligent Assistant Systems in both nominal and abnormal situations. The problem of constructing procedures is shown to be a very critical issue. In particular, keeping procedural experience in both design and operation is critical. We suggest what artificial intelligence can offer in this direction. Some crucial problems induced by this approach are discussed in detail. Finally, we analyze the various roles that would be shared by both astronauts, ground operators, and the intelligent assistant system.

Artificial intelligence approaches for rational drug design and discovery.

PubMed

Duch, Włodzisław; Swaminathan, Karthikeyan; Meller, Jarosław

2007-01-01

Pattern recognition, machine learning and artificial intelligence approaches play an increasingly important role in rational drug design, screening and identification of candidate molecules and studies on quantitative structure-activity relationships (QSAR). In this review, we present an overview of basic concepts and methodology in the fields of machine learning and artificial intelligence (AI). An emphasis is put on methods that enable an intuitive interpretation of the results and facilitate gaining an insight into the structure of the problem at hand. We also discuss representative applications of AI methods to docking, screening and QSAR studies. The growing trend to integrate computational and experimental efforts in that regard and some future developments are discussed. In addition, we comment on a broader role of machine learning and artificial intelligence approaches in biomedical research.

Artificial intelligence: the clinician of the future.

PubMed

Gallagher, S M

2001-09-01

Human beings have long been fascinated with the idea of artificial intelligence. This fascination is fueled by popular films such as Stanley Kubrick's 2001: A Space Odyssey and Stephen Spielberg's recent film, AI. However intriguing artificial intelligence may be, Hubert and Spencer Dreyfus contend that qualities exist that are uniquely human--the qualities thought to be inaccessible to the computer "mind." Patricia Benner further investigated the qualities that guide clinicians in making decisions and assessments that are not entirely evidence-based or grounded in scientific data. Perhaps it is the intuitive nature of the human being that separates us from the machine. The state of artificial intelligence is described herein, along with a discussion of computerized clinical decision-making and the role of the human being in these decisions.

Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

PubMed

Tajmir, Shahein H; Alkasab, Tarik K

2018-06-01

Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Possible Conflicts, ARRs, and Conflicts

DTIC Science & Technology

2002-05-04

Fourteenth European Conference on Artificial Intelligence Inteligencia Artificial , 41-53, (2001). (ECAI 2000), pp. 136-140, Berlin, Germany, (2000). [31] B...introduced), or proach to model-based diagnosis within the Artificial Intelligence backward (when a discrepancy is found, such as in CAEN [2, 21], community... Artificial Intelli- Relations (ARRs for short), for fault detection and localization [34]. gence community (usually known as DX). It is a research

Guidelines and rules for automated assembly by robots in space

NASA Technical Reports Server (NTRS)

Srivastava, Sadanand

1992-01-01

The development of an expert system for a 'Mechanical Design System' is discussed. Two different implementation approaches are described. One is coded in C, and the other is realized by a software package - 'Exsys.' The first method has the advantage of greater flexibility and quicker responses, while the latter one is easier to develop. This report discusses the feasible ways to establish a real mechanical intelligent design system applying artificial intelligence techniques so that the products designed by this system could best meet the requirements for space assembly.

Artificial Intelligence and Expert Systems.

ERIC Educational Resources Information Center

Wilson, Harold O.; Burford, Anna Marie

1990-01-01

Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

[Artificial intelligence in psychiatry-an overview].

PubMed

Meyer-Lindenberg, A

2018-06-18

Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) have made dramatic progress in recent years and have allowed computers to reach superhuman performance in domains that used to be thought of as uniquely human. In this overview, the underlying methodological developments that made this possible are briefly delineated and then the applications to psychiatry in three domains are discussed: precision medicine and biomarkers, natural language processing and artificial intelligence-based psychotherapeutic interventions. In conclusion, some of the risks of this new technology are mentioned.

The Hospital of the Future. Megatrends, Driving Forces, Barriers to Implementation, Overarching Perspectives, Major Trends into the Future, Implications for TATRC And Specific Recommendations for Action

DTIC Science & Technology

2008-10-01

Healthcare Systems Will Be Those That Work With Data/Info In New Ways • Artificial Intelligence Will Come to the Fore o Effectively Acquire...Education • Artificial Intelligence Will Assist in o History and Physical Examination o Imaging Selection via algorithms o Test Selection via algorithms...medical language into a simulation model based upon artificial intelligence , and • the content verification and validation of the cognitive

Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

NASA Technical Reports Server (NTRS)

Gilmore, John F. (Editor)

1987-01-01

The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

Color regeneration from reflective color sensor using an artificial intelligent technique.

PubMed

Saracoglu, Ömer Galip; Altural, Hayriye

2010-01-01

A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

Challenges facing the distribution of an artificial-intelligence-based system for nursing.

PubMed

Evans, S

1985-04-01

The marketing and successful distribution of artificial-intelligence-based decision-support systems for nursing face special barriers and challenges. Issues that must be confronted arise particularly from the present culture of the nursing profession as well as the typical organizational structures in which nurses predominantly work. Generalizations in the literature based on the limited experience of physician-oriented artificial intelligence applications (predominantly in diagnosis and pharmacologic treatment) must be modified for applicability to other health professions.

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.

Artificial Intelligence: Threat or Boon to Radiologists?

PubMed

Recht, Michael; Bryan, R Nick

2017-11-01

The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiology. But rather than being a significant threat to radiologists, we believe these changes, particularly machine learning/artificial intelligence, will be a boon to radiologists by increasing their value, efficiency, accuracy, and personal satisfaction. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Artificial Intelligence and Spacecraft Power Systems

NASA Technical Reports Server (NTRS)

Dugel-Whitehead, Norma R.

1997-01-01

This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

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.

Conversion of the CALAP (Computer Aided Landform Analysis Program) Program from FORTRAN to DUCK.

DTIC Science & Technology

1986-09-01

J’ DUCK artificial intelligence logic programming 20 AVrACT (Cthm m reerse stabN ameeaaW idelfr by block mbae) An expert advisor program named CALAP...original program was developed in FORTRAN on an HP- 1000, a mirticomputer. CALAP was reprogrammed in an Artificial Intelligence (AI) language called DUCK...the Artificial Intelligence Center, U.S. Army Engineer Topographic Laboratory, Fort Belvoir. Z" I. S. n- Page 1 I. Introduction An expert advisor

Visualization of suspicious lesions in breast MRI based on intelligent neural systems

NASA Astrophysics Data System (ADS)

Twellmann, Thorsten; Lange, Oliver; Nattkemper, Tim Wilhelm; Meyer-Bäse, Anke

2006-05-01

Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

Parallel Algorithms for Computer Vision.

DTIC Science & Technology

1989-01-01

34 IEEE Tran. Pattern Ankyaij and Ma- Artifcial Intelligence , Tokyo, 1979. chine Intelligence , 6, 1984. Kirkpatrick, S., C.D. Gelatt, Jr. and M.P. Vecchi...MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T P06010 JAN 89 ETL-0529 UNCLASSIFIED DACA76-85-C-0010 F.’G 12/1I N mommiimmmiiso...PoggioI Massachusetts Institute of Technology i Artificial Intelligence Laboratory 545 Technology Square Cambridge, Massachusetts 02139 DTIC January

Operations mission planner

NASA Technical Reports Server (NTRS)

Biefeld, Eric; Cooper, Lynne

1990-01-01

The findings are documented of the OMP research task, which investigated the applicability of artificial intelligence (AI) technology in support of automated scheduling. The goals of the effort are summarized and the technical accomplishments are highlighted. The OMP task succeeded in identifying how AI technology could be applied and demonstrated an AI-based automated scheduling approach through the OMP prototypes.

Workshop on Artificial Intelligence Applied to Materials Discovery and Design

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

None

This workshop report summarizes the presentations, panel discussions, and breakout group discussions that took place at this event. Note that the results presented here are a snapshot of the viewpoints expressed by the experts who attended the workshop and do not necessarily reflect those of the broader materials development community.

Arguing Artificially: A Rhetorical Analysis of the Debates That Have Shaped Cognitive Science.

ERIC Educational Resources Information Center

Gibson, Keith

2003-01-01

Attempts a rhetorical analysis of the history of artificial intelligence research. Responds to scholarly needs in three areas: the rhetorical nature of science, the social construction of science knowledge, and the rhetorical strategies used in artificial intelligence (AI). Suggests that this work can help rhetoricians more accurately describe the…

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

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)

Computational aerodynamics and artificial intelligence

NASA Technical Reports Server (NTRS)

Mehta, U. B.; Kutler, P.

1984-01-01

The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

PubMed

Contreras, Ivan; Vehi, Josep

2018-05-30

Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life. ©Ivan Contreras, Josep Vehi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

Simulation as an Engine of Physical Scene Understanding

DTIC Science & Technology

2013-11-05

critical to the origins of intelligence : Researchers in developmental psychology, language, animal cognition, and artificial intelligence (2–6) con- sider...implemented computationally in classic artificial intelligence systems (18–20). However, these systems have not attempted to engage with physical scene un...N00014-09-0124, N00014-07-1-0937, and 1015GNA126; by Qualcomm; and by Intelligence Advanced Research Project Activity Grant D10PC20023. 1. Marr D (1982

[Artificial intelligence in medicine: project of a mobile platform in an intelligent environment for the care of disabled and elderly people].

PubMed

Cortés, Ulises; Annicchiarico, Roberta; Campana, Fabio; Vázquez-Salceda, Javier; Urdiales, Cristina; Canãmero, Lola; López, Maite; Sánchez-Marrè, Miquel; Di Vincenzo, Sarah; Caltagirone, Carlo

2004-04-01

A project based on the integration of new technologies and artificial intelligence to develop a device--e-tool--for disabled patients and elderly people is presented. A mobile platform in intelligent environments (skilled-care facilities and home-care), controlled and managed by a multi-level architecture, is proposed to support patients and caregivers to increase self-dependency in activities of daily living.

A system for intelligent teleoperation research

NASA Technical Reports Server (NTRS)

Orlando, N. E.

1983-01-01

The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned.

A Research Planning Assessment for Applications of Artificial Intelligence in Manufacturing.

DTIC Science & Technology

1986-01-01

to apply,based on their needs.___ *PROJECT OESCRIPTION/ APPROACH : -The project will apply A_ in r’ejpesent ni ri O siri ct...of this project are essential for the practical implementation of Al-based approaches to improving unit processes. This work will enable advances in ...July 1985 to 1 August 1985. The authors wish to thank all workshop participants for their contributions to this effort. In particular, we wish to

Application of artificial neural networks to gaming

NASA Astrophysics Data System (ADS)

Baba, Norio; Kita, Tomio; Oda, Kazuhiro

1995-04-01

Recently, neural network technology has been applied to various actual problems. It has succeeded in producing a large number of intelligent systems. In this article, we suggest that it could be applied to the field of gaming. In particular, we suggest that the neural network model could be used to mimic players' characters. Several computer simulation results using a computer gaming system which is a modified version of the COMMONS GAME confirm our idea.

Center for Space Transportation and Applied Research Fifth Annual Technical Symposium Proceedings

NASA Technical Reports Server (NTRS)

1993-01-01

This Fifth Annual Technical Symposium, sponsored by the UT-Calspan Center for Space Transportation and Applied Research (CSTAR), is organized to provide an overview of the technical accomplishments of the Center's five Research and Technology focus areas during the past year. These areas include chemical propulsion, electric propulsion, commerical space transportation, computational methods, and laser materials processing. Papers in the area of artificial intelligence/expert systems are also presented.

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

PubMed

Bini, Stefano A

2018-02-27

This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in the world of health care today. We discuss the origin of AI, progress to machine learning, and then discuss how the limits of machine learning lead data scientists to develop artificial neural networks and deep learning algorithms through biomimicry. We will place all these technologies in the context of practical clinical examples and show how AI can act as a tool to support and amplify human cognitive functions for physicians delivering care to increasingly complex patients. The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it. Copyright © 2018 Elsevier Inc. All rights reserved.

A State Cyber Hub Operations Framework

DTIC Science & Technology

2016-06-01

to communicate and sense or interact with their internal states or the external environment. Machine Learning: A type of artificial intelligence that... artificial intelligence , and computational linguistics concerned with the interactions between computers and human (natural) languages. Patching: A piece...formalizing a proof of concept for cyber initiatives and developed frameworks for operationalizing the data and intelligence produced across state

Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

ERIC Educational Resources Information Center

Henard, Ralph E.

Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

Experiments in Knowledge Refinement for a Large Rule-Based System

DTIC Science & Technology

1993-08-01

empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

The Potential Role of Artificial Intelligence Technology in Education.

ERIC Educational Resources Information Center

Salem, Abdel-Badeeh M.

The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…

Demonstration of artificial intelligence technology for transit railcar diagnostics

DOT National Transportation Integrated Search

1999-01-01

This report will be of interest to railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. It documents the results of a demonstration ...

Software Reviews. PC Software for Artificial Intelligence Applications.

ERIC Educational Resources Information Center

Epp, Helmut; And Others

1988-01-01

Contrasts artificial intelligence and conventional programming languages. Reviews Personal Consultant Plus, Smalltalk/V, and Nexpert Object, which are PC-based products inspired by problem-solving paradigms. Provides information on background and operation of each. (RT)

Artificial Intelligence Assists Ultrasonic Inspection

NASA Technical Reports Server (NTRS)

Schaefer, Lloyd A.; Willenberg, James D.

1992-01-01

Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

In vitro and in vivo assessment of an intelligent artificial anal sphincter in rabbits.

PubMed

Huang, Zong-Hai; Shi, Fu-Jun; Chen, Fei; Liang, Fei-Xue; Li, Qiang; Yu, Jin-Long; Li, Zhou; Han, Xin-Jun

2011-10-01

Artificial sphincters have been developed for patients with fecal incontinence, but finding a way to make such sphincters more "intelligent" remains a problem. We assessed the function of a novel intelligent artificial anal sphincter (IAAS) in vitro and in vivo in rabbits. After the prosthesis was activated, rabbits were continent of feces during 81.4% of the activation time. The fecal detection unit provided 100% correct signals on stool in vitro and 65.7% in vivo. The results indicated that the IAAS could efficiently maintain continence and detect stool; however, the IAAS is still in the preliminary experimental stage and more work is needed to improve the system. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

NASA Technical Reports Server (NTRS)

Velez, Victor Hugo

2016-01-01

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.

Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction

NASA Astrophysics Data System (ADS)

Afan, Haitham Abdulmohsin; El-shafie, Ahmed; Mohtar, Wan Hanna Melini Wan; Yaseen, Zaher Mundher

2016-10-01

An accurate model for sediment prediction is a priority for all hydrological researchers. Many conventional methods have shown an inability to achieve an accurate prediction of suspended sediment. These methods are unable to understand the behaviour of sediment transport in rivers due to the complexity, noise, non-stationarity, and dynamism of the sediment pattern. In the past two decades, Artificial Intelligence (AI) and computational approaches have become a remarkable tool for developing an accurate model. These approaches are considered a powerful tool for solving any non-linear model, as they can deal easily with a large number of data and sophisticated models. This paper is a review of all AI approaches that have been applied in sediment modelling. The current research focuses on the development of AI application in sediment transport. In addition, the review identifies major challenges and opportunities for prospective research. Throughout the literature, complementary models superior to classical modelling.

Artificial intelligence in healthcare: past, present and future.

PubMed

Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

2017-12-01

Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.

An overview of Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET) Project

NASA Technical Reports Server (NTRS)

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

1991-01-01

A software application to assist end-users of the link evaluation terminal (LET) for satellite communications is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving (220/110 Mbps) capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. The HBR LET can determine the bit error rate (BER) under various atmospheric conditions by comparing the transmitted bit pattern with the received bit pattern. An algorithm for power augmentation will be applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions.

Artificial intelligence in healthcare: past, present and future

PubMed Central

Jiang, Fei; Jiang, Yong; Zhi, Hui; Dong, Yi; Li, Hao; Ma, Sufeng; Wang, Yilong; Dong, Qiang; Shen, Haipeng; Wang, Yongjun

2017-01-01

Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI. PMID:29507784

Modeling and Evaluating Emotions Impact on Cognition

DTIC Science & Technology

2013-07-01

Causality and Responsibility Judgment in Multi-Agent Interactions: Extended abstract. 23rd International Joint Conference on Artificial Inteligence ...responsibility judgment in multi-agent interactions." Journal of Artificial Intelligence Research v44(1), 223- 273. • Morteza Dehghani, Jonathan Gratch... Artificial Intelligence (AAAI’11). Grant related invited talks: • Keynote speaker, Workshop on Empathic and Emotional Agents at the International

Optical Inference Machines

DTIC Science & Technology

1988-06-27

de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

The 1988 Goddard Conference on Space Applications of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Rash, James (Editor); Hughes, Peter (Editor)

1988-01-01

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies.

Abstraction and reformulation in artificial intelligence.

PubMed Central

Holte, Robert C.; Choueiry, Berthe Y.

2003-01-01

This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense. PMID:12903653

Abstraction and reformulation in artificial intelligence.

PubMed

Holte, Robert C; Choueiry, Berthe Y

2003-07-29

This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense.

Integrated Artificial Intelligence Approaches for Disease Diagnostics.

PubMed

Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

2018-06-01

Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.

Artificial intelligence in cardiology.

PubMed

Bonderman, Diana

2017-12-01

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

Generalized anxiety disorder and online intelligence: A phenomenological account of why worrying is unhelpful

PubMed Central

2011-01-01

Worrying is the central feature of generalized anxiety disorder (GAD). Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to artificial intelligence and the cognitive sciences. Wheeler emphasizes the value of 'online intelligence' as contrasted to 'offline intelligence'. I discuss and apply these concepts with respect to worrying as it occurs in GAD, suggesting that GAD patients overrate the value of detached contemplation (offline intelligence), while underrating their embodied-embedded adaptive skills (online intelligence). I argue that this phenomenological account does not only help explaining why worrying is used as a coping strategy, but also why cognitive behavioral therapy is successful in treating GAD. PMID:21539727

Generalized anxiety disorder and online intelligence: a phenomenological account of why worrying is unhelpful.

PubMed

Meynen, Gerben

2011-05-03

Worrying is the central feature of generalized anxiety disorder (GAD). Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to artificial intelligence and the cognitive sciences. Wheeler emphasizes the value of 'online intelligence' as contrasted to 'offline intelligence'. I discuss and apply these concepts with respect to worrying as it occurs in GAD, suggesting that GAD patients overrate the value of detached contemplation (offline intelligence), while underrating their embodied-embedded adaptive skills (online intelligence). I argue that this phenomenological account does not only help explaining why worrying is used as a coping strategy, but also why cognitive behavioral therapy is successful in treating GAD.

A rapid prototyping/artificial intelligence approach to space station-era information management and access

NASA Technical Reports Server (NTRS)

Carnahan, Richard S., Jr.; Corey, Stephen M.; Snow, John B.

1989-01-01

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced.

Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

PubMed Central

Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

2008-01-01

Purpose To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. Methods In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. Results The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the “gold standard” specialist examination with a “refer/do not refer” decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than −7. Conclusions Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years. PMID:19277222

Artificial intelligence techniques for automatic screening of amblyogenic factors.

PubMed

Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

2008-01-01

To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the "gold standard" specialist examination with a "refer/do not refer" decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than -7. Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years.

How the strengths of Lisp-family languages facilitate building complex and flexible bioinformatics applications

PubMed Central

Khomtchouk, Bohdan B; Weitz, Edmund; Karp, Peter D; Wahlestedt, Claes

2018-01-01

Abstract We present a rationale for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Put simply, Lisp-family languages enable programmers to more quickly write programs that run faster than in other languages. Languages such as Common Lisp, Scheme and Clojure facilitate the creation of powerful and flexible software that is required for complex and rapidly evolving domains like biology. We will point out several important key features that distinguish languages of the Lisp family from other programming languages, and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSLs): languages that are specialized to a particular area, and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the ‘programmable programming language’. We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and artificial intelligence research in bioinformatics and computational biology. PMID:28040748

How the strengths of Lisp-family languages facilitate building complex and flexible bioinformatics applications.

PubMed

Khomtchouk, Bohdan B; Weitz, Edmund; Karp, Peter D; Wahlestedt, Claes

2018-05-01

We present a rationale for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Put simply, Lisp-family languages enable programmers to more quickly write programs that run faster than in other languages. Languages such as Common Lisp, Scheme and Clojure facilitate the creation of powerful and flexible software that is required for complex and rapidly evolving domains like biology. We will point out several important key features that distinguish languages of the Lisp family from other programming languages, and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSLs): languages that are specialized to a particular area, and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the 'programmable programming language'. We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and artificial intelligence research in bioinformatics and computational biology.

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

PubMed

Abbasi, Maryam; El Hanandeh, Ali

2016-10-01

Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Issues on combining human and non-human intelligence

NASA Technical Reports Server (NTRS)

Statler, Irving C.; Connors, Mary M.

1991-01-01

The purpose here is to call attention to some of the issues confronting the designer of a system that combines human and non-human intelligence. We do not know how to design a non-human intelligence in such a way that it will fit naturally into a human organization. The author's concern is that, without adequate understanding and consideration of the behavioral and psychological limitations and requirements of the human member(s) of the system, the introduction of artificial intelligence (AI) subsystems can exacerbate operational problems. We have seen that, when these technologies are not properly applied, an overall degradation of performance at the system level can occur. Only by understanding how human and automated systems work together can we be sure that the problems introduced by automation are not more serious than the problems solved.

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.

What Artificial Intelligence Is Doing for Training.

ERIC Educational Resources Information Center

Kirrane, Peter R.; Kirrane, Diane E.

1989-01-01

Discusses the three areas of research and application of artificial intelligence: (1) robotics, (2) natural language processing, and (3) knowledge-based or expert systems. Focuses on what expert systems can do, especially in the area of training. (JOW)

Third Conference on Artificial Intelligence for Space Applications, part 2

NASA Technical Reports Server (NTRS)

Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

1988-01-01

Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed.

The coming of age of artificial intelligence in medicine.

PubMed

Patel, Vimla L; Shortliffe, Edward H; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R; Bellazzi, Riccardo; Abu-Hanna, Ameen

2009-05-01

This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.

Tuberculosis control, and the where and why of artificial intelligence

PubMed Central

Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

2017-01-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

The Coming of Age of Artificial Intelligence in Medicine*

PubMed Central

Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

2009-01-01

Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

A review of European applications of artificial intelligence to space

NASA Technical Reports Server (NTRS)

Drummond, Mark (Editor); Stewart, Helen (Editor)

1993-01-01

The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

Tuberculosis control, and the where and why of artificial intelligence.

PubMed

Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

2017-04-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

Qualitative and Quantitative Proofs of Security Properties

DTIC Science & Technology

2013-04-01

Naples, Italy (September 2012) – Australasian Joint Conference on Artifical Intelligence (December 2012). • Causality, Responsibility, and Blame...realistic solution concept, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), 2009, pp. 153–158. 17. J...Conference on Artificial Intelligence (AAAI-12), 2012, pp. 1917-1923. 29. J. Y. Halpern and S. Leung, Weighted sets of probabilities and minimax

Bibliography of Research in Natural Language Generation

DTIC Science & Technology

1993-11-01

on 1397] Barbara J. Gross Focuing and description in Artifcial Intelligence (GWAI-88), Geseke, West natural language dialogues, In Joshi et al. (557...Proceedings of the Fifth Canadian Conference from information in a frame structure. Data and on Artificial Intelligence , pages Ŕ-24, London, Knowledge...generation workshops (IWNLGS, ENLGWS), natural language processing conferences (ANLP, TINLAP, SPEECH), artificial intelligence conferences (AAAI, SCA

High-Level Connectionist Models

DTIC Science & Technology

1993-04-01

The Ohio State University, Columbus Ohio. To appearto Artifcial Life IlL Angeline, P., Saunders, G., Pollack, J. (1993). An evolutionary algorithm...of Robotics and Automation, 2(1):14-23. Brooks, R. A. (1991). Intelligence without representations. Artificial Intelligence , 47:139- 159. Connell, J. H...1990). Minimalist Mobile Robotics: A Colony-style Architecture for an Creature, Volume 5 of Perspectives in Artificial Intelligence . Academic Press

Repairing Learned Knowledge Using Experience

DTIC Science & Technology

1990-05-01

34 Artifcial Intelligence Journal, vol. 19, no. 3. Winston, Patrick Henry (1984], Artificial Intelligence , Second Edition, Addison-Wesley. Analogical...process speeds up future problem solving, but the scope of the learni ng- augmented theory remains unchanged. In con- (continued on back) PD D J7 1473...Distribution/ Avaiability Codes Avail and/or .Dist Special MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1231

Temporal Reasoning and Default Logics.

DTIC Science & Technology

1985-10-01

Aritificial Intelligence ", Computer Science Research Report, Yale University, forthcoming (1985). . 74 .-, A Axioms for Describing Persistences and Clipping...34Circumscription - A Form of Non-Monotonic Reasoning", Artificial Intelligence , vol. 13 (1980), pp. 27-39. [13] McCarthy, John, "Applications of...and P. J. Hayes, "Some philosophical problems from the standpoint of artificial intelligence ", in: B. Meltzer and D. Michie (eds.), Machine

Robot Programming.

DTIC Science & Technology

1982-12-01

Paris, France, June, 1982, 519-530. Latoinbe, J. C. "Equipe Intelligence Artificielle et Robotique: Etat d’avancement des recherches," Laboratoire...8217AD-A127 233 ROBOT PROGRRMMING(U) MASSACHUSETTS INST OFGTECHi/ CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T LOZANO-PEREZ UNCLASSIFIED DC8 AI-9 N884...NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA I WORK UNIT NUMBERS ,. 545 Technology Square Cambridge

Artificial intelligence applications in the intensive care unit.

PubMed

Hanson, C W; Marshall, B E

2001-02-01

To review the history and current applications of artificial intelligence in the intensive care unit. The MEDLINE database, bibliographies of selected articles, and current texts on the subject. The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. All literature relevant to the topic was reviewed. Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

PubMed

Park, Seong Ho; Han, Kyunghwa

2018-03-01

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

The Art of Snaring Dragons. Artificial Intelligence Memo Number 338. Revised.

ERIC Educational Resources Information Center

Cohen, Harvey A.

Several models for problem solving are discussed, and the idea of a heuristic frame is developed. This concept provides a description of the evolution of problem-solving skills in terms of the growth of the number of algorithms available and increased sophistication in their use. The heuristic frame model is applied to two sets of physical…

The AMEDD Futures 2039 Project: Phase 2 Final Report

DTIC Science & Technology

2009-06-30

healthcare education. Tools such as virtual reality trainers, robotic trainers, simulations and artificial intelligence will cause self directed and...functions monitoring * robotic arm applies blood to lab-in-the-field chips * robotic self -sustaining energy sources *wireless transmission of...Biotechnology, and Robotics for Far Forward Diagnosis and Treatment of Casualties in Future Warfare – Dr. Cynthia Abbott

Expert systems research

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

Duda, R.O.; Shortliffe, E.H.

1983-04-15

Artificial intelligence, long a topic of basic computer science research, is now being applied to problems of scientific, technical, and commercial interest. Some consultation programs although limited in versatility, have achieved levels of performance rivaling those of human experts. A collateral benefit of this work is the systematization of previously unformalized knowledge in areas such as medical diagnosis and geology. 30 references.

Artificial Intelligence for Controlling Robotic Aircraft

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje

2005-01-01

A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

International experience on the use of artificial neural networks in gastroenterology.

PubMed

Grossi, E; Mancini, A; Buscema, M

2007-03-01

In this paper, we reconsider the scientific background for the use of artificial intelligence tools in medicine. A review of some recent significant papers shows that artificial neural networks, the more advanced and effective artificial intelligence technique, can improve the classification accuracy and survival prediction of a number of gastrointestinal diseases. We discuss the 'added value' the use of artificial neural networks-based tools can bring in the field of gastroenterology, both at research and clinical application level, when compared with traditional statistical or clinical-pathological methods.

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.

Decision making and problem solving with computer assistance

NASA Technical Reports Server (NTRS)

Kraiss, F.

1980-01-01

In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.

Toward a Theory of Representation Design

DTIC Science & Technology

1989-05-01

understanding. This report describes research done at the Artificial Inteligence Laboratory of the Massachusetts Institute of Technology. Support for this...AD-A210 885 Technical Report 1128 Toward a Theory of Representation Design Jeffrey Van Baale MIT Artificial Intelligence Laboratory DTIC ELECTE A... Artificial Intelligence Laboratory 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME AND ADDRESS 11. REPORT DATE Advanced Research

A Memory-Process Model of Symbolic Assimilation

DTIC Science & Technology

1974-04-01

Systems: Final Report of a Study Group, published for Artificial Intellegence by North-Holland/Amorican...contribution of the methods is answered by evaluating the same program in the context of the field of artificial intelligence. The remainder of the...been widely demonstrated on a diversity of tasks in tha history of artificial intelligence. See [r.71], chapter 2. Given a particular task to be

Supporting Organizational Problem Solving with a Workstation.

DTIC Science & Technology

1982-07-01

G. [., and Sussman, G. J. AMORD: Explicit Control or Reasoning. In Proceedings of the Symposium on Artificial Intellignece and Programming Languagues...0505 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA& WORK UNIT NUMBERS 545...extending ideas from the field of Artificial Intelligence (A), we describ office work as a problem solving activity. A knowledge embedding language called

Third Conference on Artificial Intelligence for Space Applications, part 1

NASA Technical Reports Server (NTRS)

Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

1987-01-01

The application of artificial intelligence to spacecraft and aerospace systems is discussed. Expert systems, robotics, space station automation, fault diagnostics, parallel processing, knowledge representation, scheduling, man-machine interfaces and neural nets are among the topics discussed.

On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

NASA Astrophysics Data System (ADS)

Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

2017-02-01

Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

Artificial intelligence: Learning to play Go from scratch

NASA Astrophysics Data System (ADS)

Singh, Satinder; Okun, Andy; Jackson, Andrew

2017-10-01

An artificial-intelligence program called AlphaGo Zero has mastered the game of Go without any human data or guidance. A computer scientist and two members of the American Go Association discuss the implications. See Article p.354

The systems approach for applying artificial intelligence to space station automation (Invited Paper)

NASA Astrophysics Data System (ADS)

Grose, Vernon L.

1985-12-01

The progress of technology is marked by fragmentation -- dividing research and development into ever narrower fields of specialization. Ultimately, specialists know everything about nothing. And hope for integrating those slender slivers of specialty into a whole fades. Without an integrated, all-encompassing perspective, technology becomes applied in a lopsided and often inefficient manner. A decisionary model, developed and applied for NASA's Chief Engineer toward establishment of commercial space operations, can be adapted to the identification, evaluation, and selection of optimum application of artificial intelligence for space station automation -- restoring wholeness to a situation that is otherwise chaotic due to increasing subdivision of effort. Issues such as functional assignments for space station task, domain, and symptom modules can be resolved in a manner understood by all parties rather than just the person with assigned responsibility -- and ranked by overall significance to mission accomplishment. Ranking is based on the three basic parameters of cost, performance, and schedule. This approach has successfully integrated many diverse specialties in situations like worldwide terrorism control, coal mining safety, medical malpractice risk, grain elevator explosion prevention, offshore drilling hazards, and criminal justice resource allocation -- all of which would have otherwise been subject to "squeaky wheel" emphasis and support of decision-makers.

Machine learning in laboratory medicine: waiting for the flood?

PubMed

Cabitza, Federico; Banfi, Giuseppe

2018-03-28

This review focuses on machine learning and on how methods and models combining data analytics and artificial intelligence have been applied to laboratory medicine so far. Although still in its infancy, the potential for applying machine learning to laboratory data for both diagnostic and prognostic purposes deserves more attention by the readership of this journal, as well as by physician-scientists who will want to take advantage of this new computer-based support in pathology and laboratory medicine.

Artificial intelligence: a new approach for prescription and monitoring of hemodialysis therapy.

PubMed

Akl, A I; Sobh, M A; Enab, Y M; Tattersall, J

2001-12-01

The effect of dialysis on patients is conventionally predicted using a formal mathematical model. This approach requires many assumptions of the processes involved, and validation of these may be difficult. The validity of dialysis urea modeling using a formal mathematical model has been challenged. Artificial intelligence using neural networks (NNs) has been used to solve complex problems without needing a mathematical model or an understanding of the mechanisms involved. In this study, we applied an NN model to study and predict concentrations of urea during a hemodialysis session. We measured blood concentrations of urea, patient weight, and total urea removal by direct dialysate quantification (DDQ) at 30-minute intervals during the session (in 15 chronic hemodialysis patients). The NN model was trained to recognize the evolution of measured urea concentrations and was subsequently able to predict hemodialysis session time needed to reach a target solute removal index (SRI) in patients not previously studied by the NN model (in another 15 chronic hemodialysis patients). Comparing results of the NN model with the DDQ model, the prediction error was 10.9%, with a not significant difference between predicted total urea nitrogen (UN) removal and measured UN removal by DDQ. NN model predictions of time showed a not significant difference with actual intervals needed to reach the same SRI level at the same patient conditions, except for the prediction of SRI at the first 30-minute interval, which showed a significant difference (P = 0.001). This indicates the sensitivity of the NN model to what is called patient clearance time; the prediction error was 8.3%. From our results, we conclude that artificial intelligence applications in urea kinetics can give an idea of intradialysis profiling according to individual clinical needs. In theory, this approach can be extended easily to other solutes, making the NN model a step forward to achieving artificial-intelligent dialysis control.

Autonomous and Connected Vehicles: A Law Enforcement Primer

DTIC Science & Technology

2015-12-01

CYBERSECURITY FOR AUTOMOBILES Intelligent Transportation Systems (ITS) that are emerging around the globe achieve that classification based on the convergence...Car Works,” October 18, 2011, IEEE Spectrum, http://spectrum.ieee.org/automaton/robotics/ artificial - intelligence /how-google-self-driving-car-works...whereby artificial intelligence acts on behalf of a human, but carries the same life or death consequences.435 States should encourage and engage in

Ontological Engineering and Mapping in Multiagent Systems Development

DTIC Science & Technology

2002-03-01

for knowledge engineering or artificial intelligence . Nicola Guarino compares the various definitions and the differences in their meaning in...act upon the environment through effectors [Russel and Norvig 1995]. An intelligent agent is an agent that takes the best possible action in a...situation in order to accomplish its goals. Determining what exactly characterizes the best possible action splits the field of artificial intelligence

Communication and Attitude Revision

DTIC Science & Technology

1992-01-01

Conference on Aritificial Intelligence , (1989) 1074- 1079 3. Clark, H., Marshal, C.: Definite reference and mutual knowledge. In Joshi, A., Sag, I.. and...21st Annual Meeting of the ACL (1983) 57-63 9. Konolige, K.: On the relation between default and autoepistemic logic. Artificial Intelligence 35(3...reasoning. Artificial Intelligence 13 (1980) 81-132 16. Richmond Thomason. Accommodation, meaning, and implicature. In Cohen, P., Morgan, J., and

Knowledge Based Consultation for Finite Element Structural Analysis.

DTIC Science & Technology

1980-05-01

Intelligence Finite Element Program Tutorial 20 ABSTRACT (Continue. on rees side If necessary and ide.n’ty b,’ bit,, k nionh.) In recent years, techniques of...involved in Artificial Intelligence at Stanford University developed the program MYCIN F2], for clinical consultation of diseases that require...and Rules The basic backward chaining logic, characteristic to Artificial Intelligence . approaching 1he problem of knowledge representation was

Distribution Planning: An Integration of Constraint Satisfaction & Heuristic Search Techniques

DTIC Science & Technology

1990-01-01

Proceedings of the Symposium on Aritificial Intelligence in ~~litary Logistics, Arlington, VA: American Defense Preparedness Assoc. pp. 177-182...dynamic changes, too many variables, and lack pf planning time. The Human Engineeri n ~ Laboratory (HEL) is developing artificial intelligence (AI...first attempt. The field of artificial intelligence includes a variety of knowledge-based approaches. Most widely known are Expert Systems, that are

Coordination in Distributed Intelligent Systems Applications

DTIC Science & Technology

2009-12-13

working in the area of Distributed Artificial Intelligence (DAI) unanimously endorses the idea that coordination - a fundamental paradigm - represents a...using the distributed artificial intelligence paradigm. Section 4 discusses the healthcare applications. On the other hand, Section 5 describes...coordination mechanisms should be used is in the control of swarms of UA Vs (unmanned aerial vehicles). The UAVs are considered in this case as highly mobile

Parallel Logic Programming and Parallel Systems Software and Hardware

DTIC Science & Technology

1989-07-29

Conference, Dallas TX. January 1985. (55) [Rous75] Roussel, P., "PROLOG: Manuel de Reference et d’Uilisation", Group d’ Intelligence Artificielle , Universite d...completed. Tools were provided for software development using artificial intelligence techniques. Al software for massively parallel architectures was...using artificial intelligence tech- niques. Al software for massively parallel architectures was started. 1. Introduction We describe research conducted

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)

Ethical Implications of an Experiment in Artificial Intelligence.

ERIC Educational Resources Information Center

Levinson, Stephen E.

2003-01-01

Revisits the classic debate on whether there can be an artificial creation that behaves and uses language with intelligence and agency. Argues that many moral and spiritual objections to this notion are not grounded either ethically or empirically. (Author/VWL)

Making Computers Smarter: A Look At the Controversial Field of Artificial Intelligence.

ERIC Educational Resources Information Center

Green, John O.

1984-01-01

Defines artificial intelligence (AI) and discusses its history; the current state of the art, research, experimentation, and practical applications; and probable future developments. Key dates in the history of AI and eight references are provided. (MBR)

A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

NASA Technical Reports Server (NTRS)

Hancock, Thomas M., III

1994-01-01

This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

1988 Goddard Conference on Space Applications of Artificial Intelligence, Greenbelt, MD, May 24, 1988, Proceedings

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor)

1988-01-01

This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools methodologies.

The Toulmin Argument Model in Artificial Intelligence

NASA Astrophysics Data System (ADS)

Verheij, Bart

In 1958, Toulmin published The Uses of Argument. Although this anti-formalistic monograph initially received mixed reviews (see section 2 of [20] for Toulmin’s own recounting of the reception of his book), it has become a classical text on argumentation, and the number of references to the book (when writing these words1 —by a nice numerological coincidence—1958) continues to grow (see [7] and the special issue of Argumentation 2005; Vol. 19, No. 3). Also the field of Artificial Intelligence has discovered Toulmin’s work. Especially four of Toulmin’s themes have found follow-up in Artificial Intelligence.

Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 2, Part B. Discussing, Using, and Recognizing Plans

DTIC Science & Technology

1989-03-01

1978. Williams. B.C. Qualitative Analysis of MOS Circuits. Artificial Inteligence . 1984. 24.. Wilson. K. From Association to Structure. Amsterdam:North...D-A208 378 RADC-TR-88-324, Vol II (of nine), Part B Interim Report March 1969 4. NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1987...II (of nine), Part B 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (ff ’aolicbl

JPRS Report, East Europe

DTIC Science & Technology

1987-12-08

34 artificial intelligence," on which we will also rely in the future, but once again, experience has shown that the smallest error in the construction...Western press presents such accidents as the transformation of the advantages of artificial intelligence into tragedies of artificial stupidity...life more tellingly than the recent studies con- cerning the ozone "void" discovered by satellites over the two poles, or the effects of the

Adaptive Modeling and Real-Time Simulation

DTIC Science & Technology

1984-01-01

34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

A Multiagent Based Model for Tactical Planning

DTIC Science & Technology

2002-10-01

Pub. Co. 1985. [10] Castillo, J.M. Aproximación mediante procedimientos de Inteligencia Artificial al planeamiento táctico. Doctoral Thesis...been developed under the same conceptual model and using similar Artificial Intelligence Tools. We use four different stimulus/response agents in...The conceptual model is built on base of the Agents theory. To implement the different agents we have used Artificial Intelligence techniques such

High-Level Vision and Planning Workshop Proceedings

DTIC Science & Technology

1989-08-01

Correspondence in Line Drawings of Multiple View-. In Proc. of 8th Intern. Joint Conf. on Artificial intellignece . 1983. [63] Tomiyasu, K. Tutorial...joint U.S.-Israeli workshop on artificial intelligence are provided in this Institute for Defense Analyses document. This document is based on a broad...participants is provided along with applicable references for individual papers. 14. SUBJECT TERMS 15. NUMBER OF PAGES Artificial Intelligence; Machine Vision

Efficient Effects-Based Military Planning Final Report

DTIC Science & Technology

2010-11-13

using probabilistic infer- ence methods,” in Proc. 8th Annu. Conf. Uncertainty Artificial Intelli - gence (UAI), Stanford, CA. San Mateo, CA: Morgan...Imprecise Probabilities, the 24th Conference on Uncertainty in Artificial Intelligence (UAI), 2008. 7. Yan Tong and Qiang Ji, Learning Bayesian Networks...Bayesian Networks using Constraints Cassio P. de Campos cassiopc@acm.org Dalle Molle Institute for Artificial Intelligence Galleria 2, Manno 6928

Artificial Intelligence: A Selected Bibliography.

ERIC Educational Resources Information Center

Smith, Linda C., Comp.

1984-01-01

This 19-item annotated bibliography introducing the literature of artificial intelligence (AI) is arranged by type of material--handbook, books (general interest, textbooks, collected readings), journals and newsletters, and conferences and workshops. The availability of technical reports from AI laboratories at universities and private companies…

Artificial Intelligence: Underlying Assumptions and Basic Objectives.

ERIC Educational Resources Information Center

Cercone, Nick; McCalla, Gordon

1984-01-01

Presents perspectives on methodological assumptions underlying research efforts in artificial intelligence (AI) and charts activities, motivations, methods, and current status of research in each of the major AI subareas: natural language understanding; computer vision; expert systems; search, problem solving, planning; theorem proving and logic…

Artificial Intelligence and Expert Systems.

ERIC Educational Resources Information Center

Lawlor, Joseph

Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…

Counseling, Artificial Intelligence, and Expert Systems.

ERIC Educational Resources Information Center

Illovsky, Michael E.

1994-01-01

Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

Thinking, Creativity, and Artificial Intelligence.

ERIC Educational Resources Information Center

DeSiano, Michael; DeSiano, Salvatore

This document provides an introduction to the relationship between the current knowledge of focused and creative thinking and artificial intelligence. A model for stages of focused and creative thinking gives: problem encounter/setting, preparation, concentration/incubation, clarification/generation and evaluation/judgment. While a computer can…

New approach for cognitive analysis and understanding of medical patterns and visualizations

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Tadeusiewicz, Ryszard

2003-11-01

This paper presents new opportunities for applying linguistic description of the picture merit content and AI methods to undertake tasks of the automatic understanding of images semantics in intelligent medical information systems. A successful obtaining of the crucial semantic content of the medical image may contribute considerably to the creation of new intelligent multimedia cognitive medical systems. Thanks to the new idea of cognitive resonance between stream of the data extracted from the image using linguistic methods and expectations taken from the representaion of the medical knowledge, it is possible to understand the merit content of the image even if teh form of the image is very different from any known pattern. This article proves that structural techniques of artificial intelligence may be applied in the case of tasks related to automatic classification and machine perception based on semantic pattern content in order to determine the semantic meaning of the patterns. In the paper are described some examples presenting ways of applying such techniques in the creation of cognitive vision systems for selected classes of medical images. On the base of scientific research described in the paper we try to build some new systems for collecting, storing, retrieving and intelligent interpreting selected medical images especially obtained in radiological and MRI examinations.

Knowledge structure representation and automated updates in intelligent information management systems

NASA Technical Reports Server (NTRS)

Corey, Stephen; Carnahan, Richard S., Jr.

1990-01-01

A continuing effort to apply rapid prototyping and Artificial Intelligence techniques to problems associated with projected Space Station-era information management systems is examined. In particular, timely updating of the various databases and knowledge structures within the proposed intelligent information management system (IIMS) is critical to support decision making processes. Because of the significantly large amounts of data entering the IIMS on a daily basis, information updates will need to be automatically performed with some systems requiring that data be incorporated and made available to users within a few hours. Meeting these demands depends first, on the design and implementation of information structures that are easily modified and expanded, and second, on the incorporation of intelligent automated update techniques that will allow meaningful information relationships to be established. Potential techniques are studied for developing such an automated update capability and IIMS update requirements are examined in light of results obtained from the IIMS prototyping effort.

Using Crowdsourced Geospatial Data to Aid in Nuclear Proliferation Monitoring

DTIC Science & Technology

2016-12-01

M. Stephens, and Ronald D. Bonnell, “DAI for Document Retrieval: The MINDS Project,” in Distributed Artificial Intelligence , ed. Michael N. Huhns...Ronald D. Bonnell. “DAI for Document Retrieval: The MINDS Project,” In Distributed Artificial Intelligence , edited by Michael N. Huhns, 249–283...was for the director of National Intelligence to explore ways that crowdsourced geospatial imagery technologies could aid existing governmental

DATA MAYHEM VERSUS NIMBLE INFORMATION: TRANSFORMING HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS

DTIC Science & Technology

2017-10-01

AU/ACSC/MORALES/AY17 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY DATA MAYHEM VERSUS NIMBLE INFORMATION : TRANSFORMING...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research...finding solutions to compliment and supplement human analysts’ capacity, so intelligence and information can reach operators and end-users at the

List of U.S. Army Research Institute Research and Technical Publications. Fiscal Year 2006

DTIC Science & Technology

2007-08-01

performance support systems and computer-generated simulations powered by artificial intelligence , and super-broad bandwidth. We then present a set of...dialogue, Artificial Intelligence SBIR Phase I Report 61 FY 2006 Books and Book Chapters Durlach, P.J., Neuman, J.L., & Bowens, L.D...mediation of the social intelligence -social performance relationship by social knowledge, was supported for three out of five social performance

The Analysis of Nominal Compounds,

DTIC Science & Technology

1985-12-01

34Phenomenologically plausible parsing" in Proceedings of the 1984 American Association for Aritificial Intelligence Conference, pp. 335-339. 27 Wilensky, R...34December, 1985 - CPTM #8 LJ _DTIC -5ELECTE’ DEC 1 6 198M This series of internal memos describes research in E artificial intelligence conducted under...representational techniques for natural language that have evolved in linguistics and artificial intelligence , it is difficult to find much uniformity in the

Issues in Adaptive Planning

DTIC Science & Technology

1986-06-30

approach to the application of theorem proving to problem solving, Aritificial Intelligence 2 (1Q71), 18Q- 208. 4. Fikes, R., Hart, P. and Nilsson, N...by emphasizing the structure of knowledge. 1.2. Planning Literature The earliest work in planning in Artificial Intelligence grew out of the work on...References 1. Newell, A., Artificial Intelligence and the concept of mind, in Computer models of thought and language, Schank, R. and Colby, K. (editor

Constraint-Directed Search: A Case Study of Job-Shop Scheduling.

DTIC Science & Technology

1983-12-13

Structures But Were Unable to Represent", Proceedings of the American Association for Aritificial Intelligence , pp. 212-214, Stanford University...under these constraints raises a number of issues of interest to the artificial intelligence community such as: - knowledge representation semantics for...Management Science 15 2.3. Artificial Intelligence 17 2.4. Relationship to Previous Research 21 3. ISIS Modeling System 23 3.1. Introduction 24 3.2. Layer

Framework for Evolutionary Development of an Autonomous Expert System for Acoustically Identifying Classifications of Vessels

DTIC Science & Technology

1989-01-01

completely autonomous system. SOMMIIRE Une exp6rience en intelligence artificielle (IA) en cours au CRDA vise la misc au point 6ventuelle d’un syst~me...identifying vessel classifications from 0aaV Mcute SOAifatwgms is the ultimate goal of Artificial Intelligence (Al) wod ?bhig- eouaduted -*DRAR~ An...Friendly Interface ..................................................................... 4 3 Concepts of Assistant and Autonomous Artificially Intelligent

SHRIF, a General-Purpose System for Heuristic Retrieval of Information and Facts, Applied to Medical Knowledge Processing.

ERIC Educational Resources Information Center

Findler, Nicholas V.; And Others

1992-01-01

Describes SHRIF, a System for Heuristic Retrieval of Information and Facts, and the medical knowledge base that was used in its development. Highlights include design decisions; the user-machine interface, including the language processor; and the organization of the knowledge base in an artificial intelligence (AI) project like this one. (57…

Formal verification of AI software

NASA Technical Reports Server (NTRS)

Rushby, John; Whitehurst, R. Alan

1989-01-01

The application of formal verification techniques to Artificial Intelligence (AI) software, particularly expert systems, is investigated. Constraint satisfaction and model inversion are identified as two formal specification paradigms for different classes of expert systems. A formal definition of consistency is developed, and the notion of approximate semantics is introduced. Examples are given of how these ideas can be applied in both declarative and imperative forms.

Computer finds ore

NASA Astrophysics Data System (ADS)

Bell, Peter M.

Artificial intelligence techniques are being used for the first time to evaluate geophysical, geochemical, and geologic data and theory in order to locate ore deposits. After several years of development, an intelligent computer code has been formulated and applied to the Mount Tolman area in Washington state. In a project funded by the United States Geological Survey and the National Science Foundation a set of computer programs, under the general title Prospector, was used successfully to locate a previously unknown ore-grade porphyry molybdenum deposit in the vicinity of Mount Tolman (Science, Sept. 3, 1982).The general area of the deposit had been known to contain exposures of porphyry mineralization. Between 1964 and 1978, exploration surveys had been run by the Bear Creek Mining Company, and later exploration was done in the area by the Amax Corporation. Some of the geophysical data and geochemical and other prospecting surveys were incorporated into the programs, and mine exploration specialists contributed to a set of rules for Prospector. The rules were encoded as ‘inference networks’ to form the ‘expert system’ on which the artificial intelligence codes were based. The molybdenum ore deposit discovered by the test is large, located subsurface, and has an areal extent of more than 18 km2.

Artificial Intelligence and Information Management

NASA Astrophysics Data System (ADS)

Fukumura, Teruo

After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

Artificial intelligence - New tools for aerospace project managers

NASA Technical Reports Server (NTRS)

Moja, D. C.

1985-01-01

Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

NASA Technical Reports Server (NTRS)

1994-01-01

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments.

Intelligent supercomputers: the Japanese computer sputnik

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

Walter, G.

1983-11-01

Japan's government-supported fifth-generation computer project has had a pronounced effect on the American computer and information systems industry. The US firms are intensifying their research on and production of intelligent supercomputers, a combination of computer architecture and artificial intelligence software programs. While the present generation of computers is built for the processing of numbers, the new supercomputers will be designed specifically for the solution of symbolic problems and the use of artificial intelligence software. This article discusses new and exciting developments that will increase computer capabilities in the 1990s. 4 references.

Finding Creativity in an Artificial Artist

ERIC Educational Resources Information Center

Norton, David; Heath, Derrall; Ventura, Dan

2013-01-01

Creativity is an important component of human intelligence, and imbuing artificially intelligent systems with creativity is an interesting challenge. In particular, it is difficult to quantify (or even qualify) creativity. Recently, it has been suggested that conditions for attributing creativity to a system include: appreciation, imagination, and…

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…

The Art of Artificial Intelligence. 1. Themes and Case Studies of Knowledge Engineering

DTIC Science & Technology

1977-08-01

in scientific and medical inference illuminate the art of knowledge engineering and its parent science , Artificial Intelligence....The knowledge engineer practices the art of bringing the principles and tools of AI research to bear on difficult applications problems requiring

Hybrid Applications Of Artificial Intelligence

NASA Technical Reports Server (NTRS)

Borchardt, Gary C.

1988-01-01

STAR, Simple Tool for Automated Reasoning, is interactive, interpreted programming language for development and operation of artificial-intelligence application systems. Couples symbolic processing with compiled-language functions and data structures. Written in C language and currently available in UNIX version (NPO-16832), and VMS version (NPO-16965).

Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

2003-01-01

Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

Database in Artificial Intelligence.

ERIC Educational Resources Information Center

Wilkinson, Julia

1986-01-01

Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

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)

Application of an artificial intelligence program to therapy of high-risk surgical patients.

PubMed

Patil, R S; Adibi, J; Shoemaker, W C

1996-11-01

We developed an artificial intelligence program from a large computerized database of hemodynamic and oxygen transport measurements together with prior studies defining survivors' values, outcome predictors, and a branched-chain decision tree. The artificial intelligence program was then tested on the data of 100 survivors and 100 nonsurvivors not used for the development of the program or other analyses. Using the predictor as a surrogate outcome measure, the therapy recommended by the program improved the predicted outcome 3.16% per therapeutic intervention while the actual therapy given increased outcome 1.86% in surviving patients; the artificial intelligence-recommended therapy improved outcome 7.9% in nonsurvivors, while the actual therapy given increased predicted outcome -0.29% in nonsurvivors (p < .05). There were fewer patients whose predicted outcome decreased after recommended treatment (14%) than after the actual therapy given (37%). Review of therapy recommended by the program did not reveal instances of inappropriate or potentially harmful recommendations.

Teachers and artificial intelligence. The Logo connection.

PubMed

Merbler, J B

1990-12-01

This article describes a three-phase program for training special education teachers to teach Logo and artificial intelligence. Logo is derived from the LISP computer language and is relatively simple to learn and use, and it is argued that these factors make it an ideal tool for classroom experimentation in basic artificial intelligence concepts. The program trains teachers to develop simple demonstrations of artificial intelligence using Logo. The material that the teachers learn to teach is suitable as an advanced level topic for intermediate- through secondary-level students enrolled in computer competency or similar courses. The material emphasizes problem-solving and thinking skills using a nonverbal expressive medium (Logo), thus it is deemed especially appropriate for hearing-impaired children. It is also sufficiently challenging for academically talented children, whether hearing or deaf. Although the notion of teachers as programmers is controversial, Logo is relatively easy to learn, has direct implications for education, and has been found to be an excellent tool for empowerment-for both teachers and children.

Artificial intelligence and robot responsibilities: innovating beyond rights.

PubMed

Ashrafian, Hutan

2015-04-01

The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity.

Herbert: A Second Generation Mobile Robot.

DTIC Science & Technology

1988-01-01

PROJECT. TASK S Artificial Inteligence Laboratory AREA A WORK UNIT NUMBERS ’ ~ 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME...AD-AI93 632 WMRT: A SECOND GENERTION MOBILE ROWT(U) / MASSACHUSETTS IMST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R BROOKS ET AL .JAN l8 Al-M...MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 1016 January, 1988 HERBERT: A SECOND GENERATION MOBILE ROBOT Rodney A

3D Object Recognition: Symmetry and Virtual Views

DTIC Science & Technology

1992-12-01

NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATIONI Artificial Intelligence Laboratory REPORT NUMBER 545 Technology Square AIM 1409 Cambridge... ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING A.I. Memo No. 1409 December 1992 C.B.C.L. Paper No. 76 3D Object...research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences, and at the Artificial

Artificial intelligence in the diagnosis of low back pain.

PubMed

Mann, N H; Brown, M D

1991-04-01

Computerized methods are used to recognize the characteristics of patient pain drawings. Artificial neural network (ANN) models are compared with expert predictions and traditional statistical classification methods when placing the pain drawings of low back pain patients into one of five clinically significant categories. A discussion is undertaken outlining the differences in these classifiers and the potential benefits of the ANN model as an artificial intelligence technique.

Natural Object Categorization.

DTIC Science & Technology

1987-11-01

6-A194 103 NATURAL OBJECT CATEGORIZATION(U) MASSACHUSETTS INST OF 1/3 TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R F DBICK NOY 87 AI-TR-1091 NBSSI4...ORGANI1ZATION NAME AN40 ACORES$ 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREA A WORK UNIT MUMBERS 545 Technology Square Cambridge...describes research done at the Department of Brain and Cognitive Sciences and the Artificial Intelligence Laboratory at the Massachusetts Institute of

Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.

PubMed

Alonso-Silverio, Gustavo A; Pérez-Escamirosa, Fernando; Bruno-Sanchez, Raúl; Ortiz-Simon, José L; Muñoz-Guerrero, Roberto; Minor-Martinez, Arturo; Alarcón-Paredes, Antonio

2018-05-01

A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital "Raymundo Abarca Alarcón," constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

Computers, Nanotechnology and Mind

NASA Astrophysics Data System (ADS)

Ekdahl, Bertil

2008-10-01

In 1958, two years after the Dartmouth conference, where the term artificial intelligence was coined, Herbert Simon and Allen Newell asserted the existence of "machines that think, that learn and create." They were further prophesying that the machines' capacity would increase and be on par with the human mind. Now, 50 years later, computers perform many more tasks than one could imagine in the 1950s but, virtually, no computer can do more than could the first digital computer, developed by John von Neumann in the 1940s. Computers still follow algorithms, they do not create them. However, the development of nanotechnology seems to have given rise to new hopes. With nanotechnology two things are supposed to happen. Firstly, due to the small scale it will be possible to construct huge computer memories which are supposed to be the precondition for building an artificial brain, secondly, nanotechnology will make it possible to scan the brain which in turn will make reverse engineering possible; the mind will be decoded by studying the brain. The consequence of such a belief is that the brain is no more than a calculator, i.e., all that the mind can do is in principle the results of arithmetical operations. Computers are equivalent to formal systems which in turn was an answer to an idea by Hilbert that proofs should contain ideal statements for which operations cannot be applied in a contentual way. The advocates of artificial intelligence will place content in a machine that is developed not only to be free of content but also cannot contain content. In this paper I argue that the hope for artificial intelligence is in vain.

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

PubMed

Darsey, Jerry A; Griffin, William O; Joginipelli, Sravanthi; Melapu, Venkata Kiran

2015-01-01

Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimatize to the environment or data and can maximize the chances of success or improve the efficiency of a search. Due to massive parallelism with large numbers of interconnected processers and their ability to learn from the data, neural networks can solve a variety of challenging computational problems. Neural networks have the ability to derive meaning from complicated and imprecise data; they are used in detecting patterns, and trends that are too complex for humans, or other computer systems. Solutions to the toughest problems will not be found through one narrow specialization; therefore we need to combine interdisciplinary approaches to discover the solutions to a variety of problems. Many researchers in different disciplines such as medicine, bioinformatics, molecular biology, and pharmacology have successfully applied artificial neural networks. This chapter helps the reader in understanding the basics of artificial neural networks, their applications, and methodology; it also outlines the network learning process and architecture. We present a brief outline of the application of neural networks to medical diagnosis, drug discovery, gene identification, and protein structure prediction. We conclude with a summary of the results from our study on tuberculosis data using neural networks, in diagnosing active tuberculosis, and predicting chronic vs. infiltrative forms of tuberculosis.

A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

PubMed

Kentzoglanakis, Kyriakos; Poole, Matthew

2012-01-01

In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.

Application Of Artificial Intelligence To Wind Tunnels

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Steinle, Frank W., Jr.

1989-01-01

Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

Fundamental research in artificial intelligence at NASA

NASA Technical Reports Server (NTRS)

Friedland, Peter

1990-01-01

This paper describes basic research at NASA in the field of artificial intelligence. The work is conducted at the Ames Research Center and the Jet Propulsion Laboratory, primarily under the auspices of the NASA-wide Artificial Intelligence Program in the Office of Aeronautics, Exploration and Technology. The research is aimed at solving long-term NASA problems in missions operations, spacecraft autonomy, preservation of corporate knowledge about NASA missions and vehicles, and management/analysis of scientific and engineering data. From a scientific point of view, the research is broken into the categories of: planning and scheduling; machine learning; and design of and reasoning about large-scale physical systems.

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

NASA Astrophysics Data System (ADS)

Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

2009-08-01

SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence.

PubMed

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Ruan, Wenqian; Wei, Xionghui

2018-06-01

Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima. This article summarizes the modeling and optimization of pollutants removal processes in water treatment by using multilayer perception, fuzzy neural, radial basis function and self-organizing map networks. Furthermore, the results conclude that the hybrid models of ANNs with GA and PSO can be successfully applied in water treatment with satisfactory accuracies. Finally, the limitations of current AI tools and their new developments are also highlighted for prospective applications in the environmental protection. Copyright © 2018 Elsevier Ltd. All rights reserved.

Artificial intelligence for analyzing orthopedic trauma radiographs

PubMed Central

Olczak, Jakub; Fahlberg, Niklas; Maki, Atsuto; Razavian, Ali Sharif; Jilert, Anthony; Stark, André; Sköldenberg, Olof

2017-01-01

Background and purpose — Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been applied in an orthopedic setting, and in this study we sought to determine the feasibility of using deep learning for skeletal radiographs. Methods — We extracted 256,000 wrist, hand, and ankle radiographs from Danderyd’s Hospital and identified 4 classes: fracture, laterality, body part, and exam view. We then selected 5 openly available deep learning networks that were adapted for these images. The most accurate network was benchmarked against a gold standard for fractures. We furthermore compared the network’s performance with 2 senior orthopedic surgeons who reviewed images at the same resolution as the network. Results — All networks exhibited an accuracy of at least 90% when identifying laterality, body part, and exam view. The final accuracy for fractures was estimated at 83% for the best performing network. The network performed similarly to senior orthopedic surgeons when presented with images at the same resolution as the network. The 2 reviewer Cohen’s kappa under these conditions was 0.76. Interpretation — This study supports the use for orthopedic radiographs of artificial intelligence, which can perform at a human level. While current implementation lacks important features that surgeons require, e.g. risk of dislocation, classifications, measurements, and combining multiple exam views, these problems have technical solutions that are waiting to be implemented for orthopedics. PMID:28681679

Training Software in Artificial-Intelligence Computing Techniques

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Artificial intelligence for analyzing orthopedic trauma radiographs.

PubMed

Olczak, Jakub; Fahlberg, Niklas; Maki, Atsuto; Razavian, Ali Sharif; Jilert, Anthony; Stark, André; Sköldenberg, Olof; Gordon, Max

2017-12-01

Background and purpose - Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been applied in an orthopedic setting, and in this study we sought to determine the feasibility of using deep learning for skeletal radiographs. Methods - We extracted 256,000 wrist, hand, and ankle radiographs from Danderyd's Hospital and identified 4 classes: fracture, laterality, body part, and exam view. We then selected 5 openly available deep learning networks that were adapted for these images. The most accurate network was benchmarked against a gold standard for fractures. We furthermore compared the network's performance with 2 senior orthopedic surgeons who reviewed images at the same resolution as the network. Results - All networks exhibited an accuracy of at least 90% when identifying laterality, body part, and exam view. The final accuracy for fractures was estimated at 83% for the best performing network. The network performed similarly to senior orthopedic surgeons when presented with images at the same resolution as the network. The 2 reviewer Cohen's kappa under these conditions was 0.76. Interpretation - This study supports the use for orthopedic radiographs of artificial intelligence, which can perform at a human level. While current implementation lacks important features that surgeons require, e.g. risk of dislocation, classifications, measurements, and combining multiple exam views, these problems have technical solutions that are waiting to be implemented for orthopedics.

A Sustainable City Planning Algorithm Based on TLBO and Local Search

NASA Astrophysics Data System (ADS)

Zhang, Ke; Lin, Li; Huang, Xuanxuan; Liu, Yiming; Zhang, Yonggang

2017-09-01

Nowadays, how to design a city with more sustainable features has become a center problem in the field of social development, meanwhile it has provided a broad stage for the application of artificial intelligence theories and methods. Because the design of sustainable city is essentially a constraint optimization problem, the swarm intelligence algorithm of extensive research has become a natural candidate for solving the problem. TLBO (Teaching-Learning-Based Optimization) algorithm is a new swarm intelligence algorithm. Its inspiration comes from the “teaching” and “learning” behavior of teaching class in the life. The evolution of the population is realized by simulating the “teaching” of the teacher and the student “learning” from each other, with features of less parameters, efficient, simple thinking, easy to achieve and so on. It has been successfully applied to scheduling, planning, configuration and other fields, which achieved a good effect and has been paid more and more attention by artificial intelligence researchers. Based on the classical TLBO algorithm, we propose a TLBO_LS algorithm combined with local search. We design and implement the random generation algorithm and evaluation model of urban planning problem. The experiments on the small and medium-sized random generation problem showed that our proposed algorithm has obvious advantages over DE algorithm and classical TLBO algorithm in terms of convergence speed and solution quality.

Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

ERIC Educational Resources Information Center

Borko, Harold

1985-01-01

Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

Artificial Intelligence Applications to Videodisc Technology

PubMed Central

Vries, John K.; Banks, Gordon; McLinden, Sean; Moossy, John; Brown, Melanie

1985-01-01

Much of medical information is visual in nature. Since it is not easy to describe pictorial information in linguistic terms, it has been difficult to store and retrieve this type of information. Coupling videodisc technology with artificial intelligence programming techniques may provide a means for solving this problem.

Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

1986-01-01

Describes possible applications of new technologies to special education. Discusses results of a study designed to explore the use of robotics, artificial intelligence, and computer simulations to aid people with handicapping conditions. Presents several scenarios in which specific technological advances may contribute to special education…

ICCE/ICCAI 2000 Full & Short Papers (Artificial Intelligence in Education).

ERIC Educational Resources Information Center

2000

This document contains the full and short papers on artificial intelligence in education from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a computational model for learners' motivation states in individualized tutoring system; a…

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…

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)

Artificial Intelligence in ADA: Pattern-Directed Processing. Final Report.

ERIC Educational Resources Information Center

Reeker, Larry H.; And Others

To demonstrate to computer programmers that the programming language Ada provides superior facilities for use in artificial intelligence applications, the three papers included in this report investigate the capabilities that exist within Ada for "pattern-directed" programming. The first paper (Larry H. Reeker, Tulane University) is…

Artificial Intelligence Is for Real: Undergraduate Students Should Know about It.

ERIC Educational Resources Information Center

Liebowitz, Jay

1988-01-01

Discussion of the possibilities of introducing artificial intelligence (AI) into the undergraduate curriculum highlights the introduction of AI in an introduction to information processing course for business students at George Washington University. Topics discussed include robotics, expert systems prototyping in class, and the interdisciplinary…

Progress in cybernetics and systems research. Vol. XI. Data base design. International Information Systems. Semiotic Systems. Artificial Intelligence. Cybernetics and Philosophy. Special aspects

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

Trappl, R.; Findler, N.V.; Horn, W.

1982-01-01

This book covers current research topics in six areas. These are data base design, international information systems, semiotic systems, artificial intelligence, cybernetics and philosophy, and special aspects of systems research. 1326 references.

Development of the CODER System: A Testbed for Artificial Intelligence Methods in Information Retrieval.

ERIC Educational Resources Information Center

Fox, Edward A.

1987-01-01

Discusses the CODER system, which was developed to investigate the application of artificial intelligence methods to increase the effectiveness of information retrieval systems, particularly those involving heterogeneous documents. Highlights include the use of PROLOG programing, blackboard-based designs, knowledge engineering, lexicological…

Automatic food detection in egocentric images using artificial intelligence technology

USDA-ARS?s Scientific Manuscript database

Our objective was to develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment. To study human diet and lifestyle, large sets of egocentric images were acquired using a wearable devic...

Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer.

PubMed

Ichimasa, Katsuro; Kudo, Shin-Ei; Mori, Yuichi; Misawa, Masashi; Matsudaira, Shingo; Kouyama, Yuta; Baba, Toshiyuki; Hidaka, Eiji; Wakamura, Kunihiko; Hayashi, Takemasa; Kudo, Toyoki; Ishigaki, Tomoyuki; Yagawa, Yusuke; Nakamura, Hiroki; Takeda, Kenichi; Haji, Amyn; Hamatani, Shigeharu; Mori, Kensaku; Ishida, Fumio; Miyachi, Hideyuki

2018-03-01

 Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificial intelligence can predict LNM presence, thus minimizing the need for additional surgery.  Data on 690 consecutive patients with T1 CRCs that were surgically resected in 2001 - 2016 were retrospectively analyzed. We divided patients into two groups according to date: data from 590 patients were used for machine learning for the artificial intelligence model, and the remaining 100 patients were included for model validation. The artificial intelligence model analyzed 45 clinicopathological factors and then predicted positivity or negativity for LNM. Operative specimens were used as the gold standard for the presence of LNM. The artificial intelligence model was validated by calculating the sensitivity, specificity, and accuracy for predicting LNM, and comparing these data with those of the American, European, and Japanese guidelines.  Sensitivity was 100 % (95 % confidence interval [CI] 72 % to 100 %) in all models. Specificity of the artificial intelligence model and the American, European, and Japanese guidelines was 66 % (95 %CI 56 % to 76 %), 44 % (95 %CI 34 % to 55 %), 0 % (95 %CI 0 % to 3 %), and 0 % (95 %CI 0 % to 3 %), respectively; and accuracy was 69 % (95 %CI 59 % to 78 %), 49 % (95 %CI 39 % to 59 %), 9 % (95 %CI 4 % to 16 %), and 9 % (95 %CI 4 % - 16 %), respectively. The rates of unnecessary additional surgery attributable to misdiagnosing LNM-negative patients as having LNM were: 77 % (95 %CI 62 % to 89 %) for the artificial intelligence model, and 85 % (95 %CI 73 % to 93 %; P  < 0.001), 91 % (95 %CI 84 % to 96 %; P  < 0.001), and 91 % (95 %CI 84 % to 96 %; P  < 0.001) for the American, European, and Japanese guidelines, respectively.  Compared with current guidelines, artificial intelligence significantly reduced unnecessary additional surgery after endoscopic resection of T1 CRC without missing LNM positivity. © Georg Thieme Verlag KG Stuttgart · New York.

An overview of the artificial intelligence and expert systems component of RICIS

NASA Technical Reports Server (NTRS)

Feagin, Terry

1987-01-01

Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

Human Factors Issues in the Use of Virtual and Augmented Reality for Military Purposes - USA

DTIC Science & Technology

2005-12-01

and provide a means of output, MOVES has built a prototype system and continues research into the artificial intelligence and other factors required...role in any attempt to create automaton warriors. Indeed game-theoretic notions have been utilized in applications of artificial intelligence to...Review Board at the Defense Intelligence Agency (DIA). AFRL was notified that DIA will sponsor DTNG for Certification and Accreditation. Det 4 is expected

Deductive Synthesis of the Unification Algorithm,

DTIC Science & Technology

1981-06-01

DEDUCTIVE SYNTHESIS OF THE I - UNIFICATION ALGORITHM Zohar Manna Richard Waldinger I F? Computer Science Department Artificial Intelligence Center...theorem proving," Artificial Intelligence Journal, Vol. 9, No. 1, pp. 1-35. Boyer, R. S. and J S. Moore [Jan. 19751, "Proving theorems about LISP...d’Intelligence Artificielle , U.E.R. de Luminy, Universit6 d’ Aix-Marseille II. Green, C. C. [May 1969], "Application of theorem proving to problem

Report on Ada (Trademark) Program Libraries Workshop Held at Monterey, California on November 1-3, 1983,

DTIC Science & Technology

1983-11-03

capability. An intelligent library management system will be supported by knowledge-based techniques. In fact, until a formal specification of library...from artificial intelligence and information science 2 might also be useful, for example automatic indexing and cataloging schemes, methods for fast...Artificial Intelligence 5:1045-1058, 1977. [Burstall & Goguen 801 Burstall, R. M., and Goguen, J. A. The Semantics of Clear, a Specification Language. In

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.

Reification without Evaluation.

DTIC Science & Technology

1988-06-01

PROJECT. TASK Artificial Inteligence Laboratory AREA & WORK UNIT NuMBERS ’’ 545 Technology Square 0 Cambridge, MA 02139 L $I 1, CONTROLLINO OFFICE NAME...7RD-ft" 28 REIFICRIO WITHOUT EYRURTION(U) rASSACHUSETTS INST OF 1/:LTECH CUZDGE ARTIFICI L INTELLIGENCE LUN R MEN JUN 60 RI-M-946 NM14-5-K-0-0124...themselves. This report, describes research done at, tie Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the

Construction of Optimal-Path Maps for Homogeneous-Cost-Region Path-Planning Problems

DTIC Science & Technology

1989-09-01

of Artificial Inteligence , 9%,4. 24. Kirkpatrick, S., Gelatt Jr., C. D., and Vecchi, M. P., "Optinization by Sinmulated Ani- nealing", Science, Vol...studied in depth by researchers in such fields as artificial intelligence, robot;cs, and computa- tional geometry. Most methods require homogeneous...the results of the research. 10 U. L SLEVANT RESEARCH A. APPLICABLE CONCEPTS FROM ARTIFICIAL INTELLIGENCE 1. Search Methods One of the central

Shared direct memory access on the Explorer 2-LX

NASA Technical Reports Server (NTRS)

Musgrave, Jeffrey L.

1990-01-01

Advances in Expert System technology and Artificial Intelligence have provided a framework for applying automated Intelligence to the solution of problems which were generally perceived as intractable using more classical approaches. As a result, hybrid architectures and parallel processing capability have become more common in computing environments. The Texas Instruments Explorer II-LX is an example of a machine which combines a symbolic processing environment, and a computationally oriented environment in a single chassis for integrated problem solutions. This user's manual is an attempt to make these capabilities more accessible to a wider range of engineers and programmers with problems well suited to solution in such an environment.

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

NASA Technical Reports Server (NTRS)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

DOE PAGES

Stracuzzi, David J.; Gunning, David

2015-09-28

This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.

AI in CALL--Artificially Inflated or Almost Imminent?

ERIC Educational Resources Information Center

Schulze, Mathias

2008-01-01

The application of techniques from artificial intelligence (AI) to CALL has commonly been referred to as intelligent CALL (ICALL). ICALL is only slightly older than the "CALICO Journal", and this paper looks back at a quarter century of published research mainly in North America and by North American scholars. This "inventory…

Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

The report describes three advanced technologies--robotics, artificial intelligence, and computer simulation--and identifies the ways in which they might contribute to special education. A hybrid methodology was employed to identify existing technology and forecast future needs. Following this framework, each of the technologies is defined,…

Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

ERIC Educational Resources Information Center

Burford, Anna M.; Wilson, Harold O.

This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

Command History for 1990

DTIC Science & Technology

1991-05-01

Marine Corps Tiaining Systems (CBESS) memorization training Inteligence Center, Dam Neck Threat memorization training Commander Tactical Wings, Atlantic...News Shipbuilding Technical training AEGIS Training Center, Dare Artificial Intelligence (Al) Tools Computerized firm-end analysis tools NETSCPAC...Technology Department and provides computational and electronic mail support for research in areas of artificial intelligence, computer-assisted instruction

Magical Stories: Blending Virtual Reality and Artificial Intelligence.

ERIC Educational Resources Information Center

McLellan, Hilary

Artificial intelligence (AI) techniques and virtual reality (VR) make possible powerful interactive stories, and this paper focuses on examples of virtual characters in three dimensional (3-D) worlds. Waldern, a virtual reality game designer, has theorized about and implemented software design of virtual teammates and opponents that incorporate AI…

Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

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

Stracuzzi, David J.; Gunning, David

This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.

RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

EPA Science Inventory

The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...

Artificial Intelligence and School Library Media Centers.

ERIC Educational Resources Information Center

Young, Robert J.

1990-01-01

Discusses developments in artificial intelligence in terms of their impact on school library media centers and the role of media specialists. Possible uses of expert systems, hypertext, and CD-ROM technologies in school media centers are examined and the challenges presented by these technologies are discussed. Fourteen sources of additional…

Artificial Intelligence and the High School Computer Curriculum.

ERIC Educational Resources Information Center

Dillon, Richard W.

1993-01-01

Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

Artificial Intelligence Methods in Computer-Based Instructional Design. The Minnesota Adaptive Instructional System.

ERIC Educational Resources Information Center

Tennyson, Robert

1984-01-01

Reviews educational applications of artificial intelligence and presents empirically-based design variables for developing a computer-based instruction management system. Taken from a programmatic research effort based on the Minnesota Adaptive Instructional System, variables include amount and sequence of instruction, display time, advisement,…

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

1970-01-01

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

Artificial intelligence within AFSC

NASA Technical Reports Server (NTRS)

Gersh, Mark A.

1990-01-01

Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

ERIC Educational Resources Information Center

McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

2016-01-01

Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

NASA Technical Reports Server (NTRS)

Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

1995-01-01

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system.

LOGO Progress Report 1973-1975. Artificial Intelligence Memo Number 356. Revised.

ERIC Educational Resources Information Center

Abelson, H.; And Others

This report outlines the accomplishments of the LOGO project of the Massachusetts Institute of Technology's Artificial Intelligence Laboratory during the period 1973-1975. Three major areas of work are listed: (1) building learning environments, (2) the theory behind the environments, and (3) experimenting with learning environments. Advances in…

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Survey on deep learning for radiotherapy.

PubMed

Meyer, Philippe; Noblet, Vincent; Mazzara, Christophe; Lallement, Alex

2018-07-01

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

The analysis and application of a new hybrid pollutants forecasting model using modified Kolmogorov-Zurbenko filter.

PubMed

Li, Peizhi; Wang, Yong; Dong, Qingli

2017-04-01

Cities in China suffer from severe smog and haze, and a forecasting system with high accuracy is of great importance to foresee the concentrations of the airborne particles. Compared with chemical transport models, the growing artificial intelligence models can simulate nonlinearities and interactive relationships and getting more accurate results. In this paper, the Kolmogorov-Zurbenko (KZ) filter is modified and firstly applied to construct the model using an artificial intelligence method. The concentration of inhalable particles and fine particulate matter in Dalian are used to analyze the filtered components and test the forecasting accuracy. Besides, an extended experiment is made by implementing a comprehensive comparison and a stability test using data in three other cities in China. Results testify the excellent performance of the developed hybrid models, which can be utilized to better understand the temporal features of pollutants and to perform a better air pollution control and management. Copyright © 2017 Elsevier B.V. All rights reserved.

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

NASA Technical Reports Server (NTRS)

Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

1987-01-01

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

Estimation of some transducer parameters in a broadband piezoelectric transmitter by using an artificial intelligence technique.

PubMed

Ruíz, A; Ramos, A; San Emeterio, J L

2004-04-01

An estimation procedure to efficiently find approximate values of internal parameters in ultrasonic transducers intended for broadband operation would be a valuable tool to discover internal construction data. This information is necessary in the modelling and simulation of acoustic and electrical behaviour related to ultrasonic systems containing commercial transducers. There is not a general solution for this generic problem of parameter estimation in the case of broadband piezoelectric probes. In this paper, this general problem is briefly analysed for broadband conditions. The viability of application in this field of an artificial intelligence technique supported on the modelling of the transducer internal components is studied. A genetic algorithm (GA) procedure is presented and applied to the estimation of different parameters, related to two transducers which are working as pulsed transmitters. The efficiency of this GA technique is studied, considering the influence of the number and variation range of the estimated parameters. Estimation results are experimentally ratified.

Artificial Intelligence Tools for Scaling Up of High Shear Wet Granulation Process.

PubMed

Landin, Mariana

2017-01-01

The results presented in this article demonstrate the potential of artificial intelligence tools for predicting the endpoint of the granulation process in high-speed mixer granulators of different scales from 25L to 600L. The combination of neurofuzzy logic and gene expression programing technologies allowed the modeling of the impeller power as a function of operation conditions and wet granule properties, establishing the critical variables that affect the response and obtaining a unique experimental polynomial equation (transparent model) of high predictability (R 2 > 86.78%) for all size equipment. Gene expression programing allowed the modeling of the granulation process for granulators of similar and dissimilar geometries and can be improved by implementing additional characteristics of the process, as composition variables or operation parameters (e.g., batch size, chopper speed). The principles and the methodology proposed here can be applied to understand and control manufacturing process, using any other granulation equipment, including continuous granulation processes. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Astrophysics Data System (ADS)

Szatkowski, Gerard P.; Schultz, Roger

1988-11-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

NASA Technical Reports Server (NTRS)

Szatkowski, Gerard P.; Schultz, Roger

1988-01-01

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

2015-01-01

Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

NASA Technical Reports Server (NTRS)

Yakimovsky, Y.

1974-01-01

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

Artificial Intelligence and Its Use in Cost Type analyses with an Example in Cost Performance Measurement.

DTIC Science & Technology

1985-01-01

7-Ai6i 817 ARTIFICIAL INTELLIGENCE AND ITS USE IN COST TYE1/I ANALYSES WdITH ANt EXAMPLE IN COST PERFORMANCE I MERSUREMENT(U) DEFENSE SYSTEMS...INTELLIGENCE-THE EMERGING TECHNOLOGY/ NATURAL LANGUAGE PROCESSORS K ~ With the advent of ARTIFICAL INTELLEGENCE (AI), we are entering into a new era of...language processor which is commerically available is INTELLECT, by Artifical Intellegence Incorporated, Waltham, Mass. To illustrate what a natural

Mechanical Transformation of Task Heuristics into Operational Procedures

DTIC Science & Technology

1981-04-14

Introduction A central theme of recent research in artificial intelligence is that *Intelligent task performance requires large amounts of knowledge...PLAY P1 C4] (. (LEADING (QSO)) (OR (CAN-LEAO- HEARrS (gSO)J (mEg (SUIT-OF C3) H])] C-) (FOLLOWING (QSO)) (OR [VOID (OSO) (SUIT-LED)3 [IN-SUIT C3 (SUIT...Production rules as a representation for a knowledge based consultation system. Artificial Intelligence 8:15-45, Spring, 1977. [Davis 77b] R. Davis

Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

NASA Astrophysics Data System (ADS)

Tong, S. S.

1986-01-01

The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

Artificial intelligence (AI) systems for interpreting complex medical datasets.

PubMed

Altman, R B

2017-05-01

Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability. © 2017 ASCPT.

Artificial Intelligence in Maintenance: Proceedings of the Joint Services Workshop Held at Boulder, Colorado on 4-6 October 1983.

DTIC Science & Technology

1984-06-01

intelligence . I strongly suspect that we’ll use data links to Rome so we can take advantage of both of the computer systems. Again, we see the need for close... data base indexing system would come up with a hit on those three key words I’ve just said. What is it? The hit is "artificial intelligence ." (This...pieces of data and is not classificatory in nature. In MDX there is S an intelligent data base component, called PATREC [6, 7], for doing such reasoning

Faith in the algorithm, part 1: beyond the turing test

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

Rodriguez, Marko A; Pepe, Alberto

2009-01-01

Since the Turing test was first proposed by Alan Turing in 1950, the goal of artificial intelligence has been predicated on the ability for computers to imitate human intelligence. However, the majority of uses for the computer can be said to fall outside the domain of human abilities and it is exactly outside of this domain where computers have demonstrated their greatest contribution. Another definition for artificial intelligence is one that is not predicated on human mimicry, but instead, on human amplification, where the algorithms that are best at accomplishing this are deemed the most intelligent. This article surveys variousmore » systems that augment human and social intelligence.« less

The dynamic lift of developmental process.

PubMed

Smith, Linda B; Breazeal, Cynthia

2007-01-01

What are the essential properties of human intelligence, currently unparalleled in its power relative to other biological forms and relative to artificial forms of intelligence? We suggest that answering this question depends critically on understanding developmental process. This paper considers three principles potentially essential to building human-like intelligence: the heterogeneity of the component processes, the embedding of development in a social world, and developmental processes that change the cognitive system as a function of the history of soft-assemblies of these heterogeneous processes in specific tasks. The paper uses examples from human development and from developmental robotics to show how these processes also may underlie biological intelligence and enable us to generate more advanced forms of artificial intelligence.

Collective intelligence of the artificial life community on its own successes, failures, and future.

PubMed

Rasmussen, Steen; Raven, Michael J; Keating, Gordon N; Bedau, Mark A

2003-01-01

We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.

Artificial intelligence in medicine: the challenges ahead.

PubMed

Coiera, E W

1996-01-01

The modern study of artificial intelligence in medicine (AIM) is 25 years old. Throughout this period, the field has attracted many of the best computer scientists, and their work represents a remarkable achievement. However, AIM has not been successful-if success is judged as making an impact on the practice of medicine. Much recent work in AIM has been focused inward, addressing problems that are at the crossroads of the parent disciplines of medicine and artificial intelligence. Now, AIM must move forward with the insights that it has gained and focus on finding solutions for problems at the heart of medical practice. The growing emphasis within medicine on evidence-based practice should provide the right environment for that change.

Analysis of the frontier technology of agricultural IoT and its predication research

NASA Astrophysics Data System (ADS)

Han, Shuqing; Zhang, Jianhua; Zhu, Mengshuai; Wu, Jianzhai; Shen, Chen; Kong, Fantao

2017-09-01

Agricultural IoT (Internet of Things) develops rapidly. Nanotechnology, biotechnology and optoelectronic technology are successfully integrated into the agricultural sensor technology. Big data, cloud computing and artificial intelligence technology have also been successfully used in IoT. This paper carries out the research on integration of agricultural sensor technology, nanotechnology, biotechnology and optoelectronic technology and the application of big data, cloud computing and artificial intelligence technology in agricultural IoT. The advantages and development of the integration of nanotechnology, biotechnology and optoelectronic technology with agricultural sensor technology were discussed. The application of big data, cloud computing and artificial intelligence technology in IoT and their development trend were analysed.

Structural analysis of peptides that fill sites near the active center of the two different enzyme molecules by artificial intelligence and computer simulations

NASA Astrophysics Data System (ADS)

Nishiyama, Katsuhiko

2018-05-01

Using artificial intelligence, the binding styles of 167 tetrapeptides were predicted in the active site of papain and cathepsin K. Five tetrapeptides (Asn-Leu-Lys-Trp, Asp-Gln-Trp-Gly, Cys-Gln-Leu-Arg, Gln-Leu-Trp-Thr and Arg-Ser-Glu-Arg) were found to bind sites near the active center of both papain and cathepsin K. These five tetrapeptides have the potential to also bind sites of other cysteine proteases, and structural characteristics of these tetrapeptides should aid the design of a common inhibitor of cysteine proteases. Smart application of artificial intelligence should accelerate data mining of important complex systems.

Inspection Methods in Programming: Cliches and Plans.

DTIC Science & Technology

1987-12-01

PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREA & WORK UN IT NUMBERS J 545 Technology Square Cambridge, MA 02139 $L. CONTROLLING...U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB C RICH DEC 87 AI-M-±05 UNCLASSIFIED NW014-B5-K-0124 F/G 12/5 NL ’lllll l l l...S %P W. J % % %s MASSACHUSETTS INSTITUTE OF TECHNOLOGY N ARTIFICIAL INTELLIGENCE LABORATORY 00 A.I. Memo No. 1005 December 1987 N Inspection Methods

Planning and Problem Solving

DTIC Science & Technology

1982-10-01

Artificial Intelig ~ence (Vol. III, edited by Paul R. Cohen and’ Edward A.. Feigenbaum)’, The chapter was written B’ Paul Cohen, with contributions... Artificial Intelligence (Vol. III, edited by Paul R. Cohen and EdWard A. Feigenbaum). The chapter was written by Paul R. Cohen, with contributions by Stephen...Wheevoats"EntermdI’ Planning and Problem ’Solving by Paul R. Cohen Chaptb-rXV-of Volumec III’of the Handbook of Artificial Intelligence edited by Paul R

Mission Profiles and Evidential Reasoning for Estimating Information Relevancy in Multi-Agent Supervisory Control Applications

DTIC Science & Technology

2010-06-01

artificial agents, their limited scope and singular purpose lead us to believe that human-machine trust will be very portable. That is, if one operator... Artificial Intelligence Review 2(2), 1988. [E88] M.R. Endsley. Situation awareness global assessment technique (SAGAT). In Proceedings of the National...1995. [F98] J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Addison- Wesley, 1998. [NP01] I. Niles and A

Survey of Artificial Intelligence and Expert Systems in Library and Information Science Literature.

ERIC Educational Resources Information Center

Hsieh, Cynthia C.; Hall, Wendy

1989-01-01

Examines the definition and history of artificial intelligence (AI) and investigates the body of literature on AI found in "Library Literature" and "Library and Information Science Abstracts." The results reported include the number of articles by year and per journal, and the percentage of articles dealing with library…

Artificial Intelligence Applications to Learning and Training. Occasional Paper--InTER/2/88.

ERIC Educational Resources Information Center

Cumming, Geoff

This report summarizes and interprets the discussions at a seminar on artificial intelligence (AI) training domains and knowledge representations which was sponsored by the United Kingdom Training Commission. The following broad areas are addressed: (1) the context, process, and diversity of requirements of training and training needs; (2)…

Artificial Intelligence, Counseling, and Cognitive Psychology.

ERIC Educational Resources Information Center

Brack, Greg; And Others

With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…

Artificial Intelligence: Themes in the Second Decade. Memo Number 67.

ERIC Educational Resources Information Center

Feigenbaum, Edward A.

The text of an invited address on artificial intelligence (AI) research over the 1963-1968 period is presented. A survey of recent studies on the computer simulation of intellective processes emphasizes developments in heuristic programing, problem-solving and closely related learning models. Progress and problems in these areas are indicated by…

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…

Turtle Escapes the Plane: Some Advanced Turtle Geometry. Artificial Intelligence Memo Number 348.

ERIC Educational Resources Information Center

diSessa, Andy

The LOGO Turtles, originally developed at the Massachusetts Institute of Technology Artificial Intelligence Laboratory for teaching concepts in elementary geometry to primary-age children, can also be used in teaching higher-level mathematics. In the exercises described here, the turtle was programed to traverse curved surfaces. Both geometric and…

Application of artificial intelligence to risk analysis for forested ecosystems

Treesearch

Daniel L. Schmoldt

2001-01-01

Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI)...

Exploiting Artificial Intelligence To Enhance Training: A Short- and Medium-Term Perspective.

ERIC Educational Resources Information Center

Cumming, Geoff

This paper is an introductory discussion of industrial training, artificial intelligence (AI), and AI applications in training, prepared in the context of the United Kingdom Training Commission (TC) program. Following an outline of the activities and aims of the program, individual sections describe perspectives on: (1) training needs, including…

A Retrospective and Prospective View of Information Retrieval and Artificial Intelligence in the 21st Century.

ERIC Educational Resources Information Center

Garfield, Eugene

2001-01-01

Traces the development of information retrieval/services and suggests that the creation of large digital libraries seems inevitable. Examines possibilities for increasing electronic access and the role of artificial intelligence. Highlights include: searching full text; sending full texts; selective dissemination of information (SDI) profiling and…

Artificial Intelligence, Computational Thinking, and Mathematics Education

ERIC Educational Resources Information Center

Gadanidis, George

2017-01-01

Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…

Automated Management Of Documents

NASA Technical Reports Server (NTRS)

Boy, Guy

1995-01-01

Report presents main technical issues involved in computer-integrated documentation. Problems associated with automation of management and maintenance of documents analyzed from perspectives of artificial intelligence and human factors. Technologies that may prove useful in computer-integrated documentation reviewed: these include conventional approaches to indexing and retrieval of information, use of hypertext, and knowledge-based artificial-intelligence systems.

Artificial Intelligence Software Acquisition Program. Volume 2.

DTIC Science & Technology

1987-12-01

34Architect tire prototyping in the software engineering environment". 1BBA! .’ qtins Jo urnal, vol. 23, No. 1, p. 4-18, 1984. 3v Boehmi, Barry W_. Gray...on Artificial Intelligence, Sponsored by AAAI, December 1986. ..- ~[31] Pressman , Roger S. "Software Engineering: A Practitioner’s Approach". McGraw

An Artificial Intelligence Approach to the Symbolic Factorization of Multivariable Polynomials. Technical Report No. CS74019-R.

ERIC Educational Resources Information Center

Claybrook, Billy G.

A new heuristic factorization scheme uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with interger coefficients and an arbitrary number of variables and terms. The factorization scheme makes extensive use of artificial intelligence techniques (e.g., model-building, learning, and…