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Artificial Intelligence, Expert Systems, Neural Networks and Knowledge Based Systems

Technical Resources

These pages provide access to a wealth of information (including FAQs) about Artificial Intelligence ( AI ). Information can be found on a diversity of related subjects including Artificial Life, Bayesian Belief Networks, Data Mining, Decision Support, Decision Analysis, Risk Analysis, DSS, Expert Systems, Fuzzy Logic, Genetic Algorithms, Help Desk, Knowledge Based Systems ( KBS ), Neural Networks and Simulation Technology

Artifical Intelligence | Bayesian (Belief) Networks | Expert Systems | Fuzzy logic | Genetic algorithms | Genetic programming | Knowledge Based Systems | Knowledge Management | Neural Networks | Pattern recognition |

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Artifical Intelligence
 AI on the Web (Stuart Russell)
 AI Programming Languages FAQs (CMU Artificial Intelligence Repository)
 AI Repositories and Resource Lists (CMU Artificial Intelligence Repository)
 AI resources (Stottler Henke Associates, Inc)
 AI Resources (American Association for Artificial Intelligence (AAAI))
  One of the big questions of science is "What is intelligence?" Artificial intelligence is the study of intelligence--in machines and, through computers, in people. Much of the general information listed in this section is concerned with the nature of the science and the question of whether computers can think. Most of the other pages in About AI are concerned with how to build computers that think.
 Alife Database - Code Sharing Oriented (Ariel Dolan)
  "The Alife Database is a searchable database of Alife-related sites on the world wide web. Its initial purpose was to encourage code sharing in the Alife community by making it easy to find Alife code on the net. It is still primarily oriented towards active Alife participation, and therefore it puts an emphasis on sites offering free source code (especially Java) and on sites providing online playing and experimenting.The emphasis on Java is based on the fact that Java supports both cross-platform code sharing and online experimenting better then any other programming language."
 An Introduction to the Science of Artificial Intelligence
  Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent. The ability to create intelligent machines has intrigued humans since ancient times, and today with the advent of the computer and 50 years of research into AI programming techniques, the dream of smart machines is becoming a reality. Researchers are creating systems which can mimic human thought, understand speech, beat the best human chessplayer, and countless other feats never before possible. Find out how the military is applying AI logic to its hi-tech systems, and how in the near future Artificial Intelligence may impact our lives.
 Artifcial Intelligence - Subject Index (National Research Council, Canada)
  Over 30 technical areas based on Artificial Intelligence
 Artificial Intelligence (Galaxy Database)
 Artificial Intelligence (PC AI) (Knowledge Technology, Inc)
  An AI program that models the nuances of the human thought process or solves complicated real-world problems can be complex. Languages for building AI programs have the capacity to that take care of low-level computing processes, thus allowing the developer to focus on the requisite complexity. AI programs work with concepts expressed in words, phrases, or sentences. Therefore, the ability to handle symbolic (i.e., non-numeric) data is an important feature. To develop an AI system, a programmer tries numerous ways of implementing each constituent function. Rather than go through a lengthy edit-compile-debug cycle to test each rendition of a function, an AI language should allow the programmer to quickly see the results of a new idea. Languages that feature interactive programming address this need. Programmer can not anticipated the exact type or quantity of data that flows through a program, so the must adapt on the fly. A language that incorporates flexible data structures allows this happen in an easy, natural way. Many types of inference processes recur throughout an AI applications. A language that has one or more of these processes built-in can save time and effort.
 Artificial Intelligence FAQs (CMU AI Repository)
 Artificial Intelligence FAQs
 Artificial Intelligence Information Sources (ACM)
 Artificial Intelligence News Groups
 Artificial Intelligence Repository (Carnegie Mellon University's CSU)
 Artificial Intelligence Resources (National Reseacrch Council, Canada)
  These are some Internet resources that may be useful to AI researchers.
 Artificial Intelligence Shareware (Industry.Net)
 Artificial Life Online Library
  This is a list of on-line Alife papers. This includes ones on genetic programming, learning, autonomous agents, robotics, and evolution.
 Automated Deduction links (Tomas Uribe)
  This collection of papers and FTP sites is focused mostly on Automated Deduction and related matters
 Cognitive Systems (Pacific Northwest National Laboratory)
  A collection of emerging information technologies inspired by the qualitative nature of biologically based information processing which is found in the nervous system, human reasoning, human decision making, and natural selection. These include artificial neural networks, fuzzy logic, evolutionary computation, knowledge-based systems, and artificial intelligence and draw on the advances in neuroscience, cognitive science, and computer science.
 Compinfo Directory: Intelligent Agents
 Compinfo Directory: Voice and Speech Technologies
 Cyc FAQ (Jorn Barger)
  CYC is the name of a very large, multi-contextual knowledge base and inference engine, the development of which started at the Microelectronics and Computer Technology Corporation (MCC) in Austin, Texas during the early 1980s.
 Journal of Artificial Intelligence Research
  JAIR covers all areas of artificial intelligence (AI), publishing refereed research articles, survey articles, and technical notes
 Mechanised (or Automated) Reasoning (Michael Kohlhase and Carolyn Talcott.)
  "To understand what automated reasoning is, we must first understand what reasoning is. Reasoning is the process of drawing conclusions from facts. For the reasoning to be sound, these conclusions must follow inevitably from the facts from which they are drawn. In other words, reasoning [...] is not concerned with some conclusion that has a good chance of being true when the facts are true. Indeed, reasoning as used here refers to logical reasoning, not of common-sense reasoning or probabilistic reasoning. The only conclusions that are acceptable are those that follow logically from the supplied facts. The object of automated reasoning is to write computer programs that assist in solving problems and in answering questions requiring reasoning. The assistance provided by an automated reasoning program is available in two different modes. You can use such a program in an iterative fashion; that is, you can instruct it to draw some conclusions and present them to you, and then, based on your analysis of the conclusions, it can in the next run execute your new set of instructions. Or you can use such a program in a batch mode; that is, you can assign it an entire reasoning task and await the final result." (Larry Wos; Ross Overbeek; Ewing Lusk; Jim Boyle: Automated reasoning: Introduction and Applications. McGraw Hill 1992.)
 Navy Center for Applied Research in Artificial Intelligence
  The Navy Center for Applied Research in Artificial Intelligence (NCARAI) has been involved in both basic and applied research in artificial intelligence since its inception in 1982. NCARAI, part of the Information Technology Division within the Naval Research Laboratory, is engaged in research and development efforts designed to address the application of artificial intelligence technology and techniques to critical Navy and national problems.
 Neuron AI Directory (Neuron Technology)
  A directory covering a range of subjects including artificial intelligence, artificial life, artificial neural networks, experts systems, fuzzy logic, genetic algorithms and natural language processing
 Other AI Starting Points (Hugin)
 SIGART Electronic Information Service
  SIGART is the ACM Special Interest Group on Artificial Intelligence. The EIS serves as a repository for AI related resources and information.
 Terms and definitions - Artificial Intelligence (PC Webopedia)
  See this page for definition of these terms: agent, artificial intelligence, bot, cybernetics, expert system, fuzzy logic, genetic programming, handwriting recognition, language, natural language, neural network, optical character recognition, pattern recognition, robot, robotics, voice recognition
 The World Wide Web Virtual Library: Artificial Intelligence
Bayesian (Belief) Networks
 Bayesian Belief Network Application Group
  Bayesian Belief Networks (BBNs) are at the cutting edge of expert systems research and development. Unlike the traditional rule-based approach to expert systems, they are able to replicate the essential features of plausible reasoning (reasoning under conditions of uncertainty) in a consistent, efficient and mathematically sound way. Critically they are able to retract belief in a particular case when the basis of that belief is explained away by new evidence. Since most real life problems involve inherently uncertain relationships, BBN is a technology with huge potential for application across many domains.
 Bayesian Networks and Software Metrics Resources (Agena Ltd.)
Expert Systems
 Expert System Shells FAQ
 Expert Systems Interest Group - Resources (American Bar Association)
  "Knowledge-based expert systems, or simply expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems." (PC AI)
Fuzzy logic
 Center for Fuzzy Logic, Robotics, and Intelligent Systems
  The Center for Fuzzy Logic, Robotics , and Intelligent Systems (CFL) at Texas A&M; University is one of the leading research organizations in the nation focusing on multi-disciplinary research related to intelligent systems and their applications in Engineering Systems. The research activities of the Center cover emerging technologies including Fuzzy Logic, Robotics, and Artificial Intelligence.
 Fuzzy Logic and Neurofuzzy resources (Southampton University)
 Perceptual Science Laboratory , UCSC
  The Perceptual Science Laboratory is engaged in a variety of experimental and theoretical inquiries in perception and cognition. A major research area concerns speech perception by ear and eye, and facial animation. We also have tested a general fuzzy logical model of perception in a variety of domains, including perception and understanding of language, memory, object, shape and depth perception, learning, and decision making. Research is also being carried out in reading.
Genetic algorithms
 The Genetic Algorithms Archive
  The Genetic Algorithms Archive is a repository for information related to research in genetic algorithms and other forms of evolutionary computation. Available from this site are past issues of the GA-List digest, source code for many GA implementations, and announcements about GA-related conferences. Also, links are given to many interesting sites around the World with material related to evolutionary computation
Genetic programming
 Genetic Programming (CSD, UCL)
 The Genetic Programming Notebook (Jaime Fernandez)
  Genetic programming is a branch of genetic algorithms. The main difference between genetic programming and genetic algorithms is the representation of the solution. Genetic programming creates computer programs in the lisp or scheme computer languages as the solution. Genetic algorithms create a string of numbers that represent the solution
Knowledge Based Systems
 Machine Discovery Terminology
  Machine Discovery develops discovery methods and discovery systems to support knowledge discovery processes, which, in its turn, seeks new knowledge about an application domain.
Knowledge Management
 Decision Support Systems and Knowledge Management - Internet resources (University of Kentucky)
  This page provides access to Decision Support and Knowledge Management resources
 Knowledge Management Consortium International
  Organizations and individuals coming together to develop a shared vision, common understanding, and aligned action about Knowledge and Knowledge Management.
 Knowledge Management Forum
 Knowledge Management resources (Buckman Laboratories)
  Contains books, articles, journals, websites and other references, as well as related topics like culture change, leadership, measurement and information technology.
 Resource Center on Knowledge Management (I.T. Works bvba)
 Sveiby Knowledge Management Library (Karl Erik Sveiby)
  Karl Sveiby has researched management of knowledge and knowledge organizations since the early 1980s, which makes him a veteran in the Knowledge Management field. This is a collection of his writings
 What Is Knowledge Management
  Knowledge Management is the collection of processes that govern the creation, dissemination, and utilization of knowledge. In one form or another, knowledge management has been around for a very long time. Practitioners have included philosophers, priests, teachers, politicians, scribes, Liberians, etc.
Neural Networks
 An Introduction To Neural Networks (Z Solutions, LLC)
 IEEE Neural Network Council
  The field of interest of the Council and its activities and programs shall be the theory, design, application and development of biologically and linguistically motivated computational paradigms emphasizing neural networks, including connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained.
 Neural network and neuroscience links (Ric Lister)
 Neural Network Labs around the world (Ric Lister)
 Neural Networks FAQs (Warren S. Sarle)
 Neural Networks Shareware (
 Neurality --> NeuroLinks (ICE srl)
  Demos and tutorials about Neural Networks
 NeuroComputing Web - Neural Computing Technology Transfer Programme (UK's DTI)
Pattern recognition
 Pattern and Information Processing Group (David Whitaker, Defence Research Agency)
 Pattern Recognition Information (Bob Duin, Delft University Pattern Recognition Group)
  Pattern recognition is the research area that studies the operation and design of systems that recognize patterns in data. It encloses subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern recognition), grammatical inference and parsing (sometimes called syntactical pattern recognition). Important application areas are image analysis, character recognition, speech analysis, man and machine diagnostics, person identification and industrial inspection.
 Pattern Recognition resources (Image, Speech and Intelligent Systems research group, University of Sothampton, UK)
  This covers research groups, software, journals, test data and others


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