AI Lab Of The EPFL Research in constraint satisfaction, modelbased reasoning, case-based reasoning,intelligent agents, and natural language processing. http://liawww.epfl.ch/
Databases And Artificial Intelligence 3 Databases and artificial intelligence 3 artificial intelligence Segment artificial intelligence Programming in Prolog artificial intelligence http://www.cee.hw.ac.uk/~alison/ai3notes/all.html
Extractions: Tradingsystems for many stocks! A tradingsystem gives you a system to trade a stock. To trade a stock means to buy and sell this stock according to the underlying tradingsystem. Many traders use tradingsystems in order to beat the stock market. Using a tradingsystem for a stock doesn't guarantee big profit, but can help to increase the profit without a tradingsystem. Of course, trading stocks with a tradingsystem is no guarantee to make big profits. Tradingsystems based on artificial intelligence bring a new perspective in trading stocks. Artificial intelligence is used at AI-Trader to form a tradingsystem for stocks. Each tradingsystem is unique, whcih means a tradingsystem for stock A is completely different from a tradingsystem for stock B. Now enjoy our fine tradingsystems based on artificial intelligence at AI-Trader!
Generation5 - John Searle A short interview focusing on Searle's views concerning artificial intelligence. http://www.generation5.org/searle.shtml
Extractions: Printable Version John Searle , Professor of Philosophy at Berkeley, is best known for his famous "Chinese Room" Analogy. The analogy goes like this: Dr. Searle is in a large room with two holes marked I (Input) and O (Output). From the 'I' box, he gets handed questions written in Chinese kanji . Also in his room is a huge book with English instructions as to how to look up the answers and write them on a piece of paper to the Chinese questions - therefore, practicalities aside, he could look up any question and give the right answer. Searle says this is analogous to computers running NLP programs just because they input the correct answer given an input, no matter how complicated the algorithm, it does not constitute understanding The analogy has been a huge area of debate for the twenty years that has passed since Dr. Searle first published his paper on it. Generation5 is very proud to have had the chance to interview him. Glossary Chinese Room, The
Home Page For School Of Computer Science And Software Engineering School of Computer Science and Software Engineering. Research areas include artificial intelligence; audiovisual information processing; digital systems hardware; computing education; database systems; distributed, parallel and mobile computing; logic and theory; reasoning under uncertainty; and software engineering. http://www.csse.monash.edu.au/
Extractions: Skip to content Change text size About CSSE Courses ... Site map SEARCH Computer Science and Software Engineering Information Technology All of Monash CSSE Computer Science and Software Engineering About CSSE General Information, Location, Contact details, History. Courses Degrees, Courses, Handbook Entries. People Staff, Students, Alumni. Research Research Groups, Publications, Seminars. Student Information On-line Coursework, Subjects, Timetables, Important Dates, Student Club. Community Jobs, Smarthouse Project, Open Day, Schools Liason Activities. Mostly restricted access. Latest News Monash University ABN 12 377 614 012 - Caution CRICOS Provider Number: 00008C
Artificial Intelligence Originating in artificial intelligence with the study of robot learning and modelsof natural learning, it has led to spinoffs like neural and evolutionary http://www.ai.cse.unsw.edu.au/
Extractions: Last updated Home People Publications AI Seminars ... Contact The following are the main research areas in our group. There are many other areas of interest persued by individual researchers - please consult their respective home pages for more details. Knowledge Acquisition : Knowledge Acquisition is concerned with the development of knowledge bases based on the expertise of a human expert. This requires to express knowledge in a formalism suitable for automatic interpretation. Within this field, research at UNSW focusses on incremental knowledge acquisition techniques, which allow a human expert to provide explanations of their decisions that are automatically integrated into sophisticated knowledge bases. Knowledge Representation and Reasoning : Knowledge representation and reasoning deals with the formal aspects of representing and modelling problem domains and then reasoning with these representations. A key focus is the tradeoff between the expressiveness of the representation and the complexity of the associated reasoning algorithms. Machine Learning : Machine learning is the computational approach to learning from data. Originating in artificial intelligence with the study of robot learning and models of natural learning, it has led to spin-offs like neural and evolutionary computation, data mining, learning theory and program synthesis. The techniques have been applied in just about every current data-intensive area of activity.
Politecnico Di Milano Department of Electronics and Computing. Research areas include artificial intelligence and robotics, computer architecture, databases and information systems, multimedia, software engineering, theoretical computer science, http://www.elet.polimi.it/
Brown CS: Artificial Intelligence artificial intelligence at Brown University is concerned with theoretical andempirical studies involving problems ranging from natural language http://www.cs.brown.edu/research/ai/
Extractions: You are in the: Small Business Computing Channel View Sites + ECommerce-Guide Small Business Computing ... »Close Enter a word for a definition... ...or choose a computer category. choose one... All Categories Communications Computer Industry Companies Computer Science Data Graphics Hardware Internet and Online Services Mobile Computing Multimedia Networks Open Source Operating Systems Programming Software Standards Types of Computers Wireless Computing World Wide Web Home artificial intelligence Last modified: Tuesday, February 10, 2004 The branch of computer science concerned with making computers behave like humans. The term was coined in 1956 by John McCarthy at the Massachusetts Institute of Technology. Artificial intelligence includes games playing: programming computers to play games such as chess and checkers expert systems programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms) natural language programming computers to understand natural human languages neural networks Systems that simulate intelligence by attempting to reproduce the types of physical connections that occur in animal brains robotics programming computers to see and hear and react to other sensory stimuli Currently, no computers exhibit full artificial intelligence (that is, are able to simulate human behavior). The greatest advances have occurred in the field of games playing. The best computer chess programs are now capable of beating humans. In May, 1997, an IBM super-computer called
Julia Hodges's Computer Science Home Page Mississippi State University artificial intelligence, knowledge representation, knowledge discovery in databases, expert systems, document understanding. http://www.cs.msstate.edu/~hodges
Extractions: E-Mail Address: hodges@cse.msstate.edu For a list of recent papers and reports by Dr. Hodges, click here. For more information on the AI research activities in the Department of Computer Science and Engineering, click here. For information about the TA Practicum, click here. For information about CSE 4503/6503 in Fall 2005, click here. For the regulations regarding after-hours access to Butler Hall, click here.
IngentaConnect Publication: Applied Artificial Intelligence Applied artificial intelligence. ISSN 08839514 visit publication homepage Applied artificial intelligence logo Taylor and Francis Ltd logo http://www.ingentaconnect.com/content/tandf/uaai
Extractions: visit publication homepage Publisher: Taylor and Francis Ltd issues are available electronically Volume 19 Number 7, August 2005 Number 6, July 2005 Numbers 3-4, -4/Mar 2005 Number 1, February 2005 Volume 18 Number 8, September 2004 Number 7, August 2004 Number 6, July 2004 Number 2, February 2004 ... Number 1, January 2004 Volume 17 Number 10, November-December 2003 Numbers 8-9, Numbers 8-9/September-October 2003 Number 7, August 2003 Numbers 5-6, Numbers 5-6/May-July 2003 ... Number 1, January 2003 Volume 16 Numbers 9-10, 1 October 2002
Push Singh MIT Media Lab artificial intelligence, open source web collaborations, leader of Open Mind Commonsense project. http://www.media.mit.edu/people/push/
Extractions: Phone: (617) 253-1750 Weblog pushsingh.blogspot.com Background Research Publications ... Random Background Until recently, I was a Ph.D. student in the department of EECS at MIT . I am now a Postdoctoral Associate at the MIT Media Lab . My research is focused on finding ways to give computers human-like common sense , the ability to think about the everyday world like people do. I believe this will enable a new generation of computing systems that will be much more powerful and friendly than those based on present-day technologies. I am actively pushing a project at the Media Lab to develop programs capable of commonsense thinking. This is a very hands-on effort to build a suite of commonsense knowledge bases, inference engines, and architectural elements for linking these together, as well as new kinds of applications built on these technologies. These systems use multiple representations including semantic networks, propositional and first-order probabilistic graphical models, case bases of story scripts, rule based systems, logical axioms, shape descriptions, and even English sentences. For more details about this effort please visit the Media Lab's Commonsense Computing web page.
2002 Australasian Natural Language Processing Workshop 2 December 2002, Canberra, Australia. To be held in conjunction with the 15th Australian Joint Conference on artificial intelligence (AI'02). Organized by the Centre for Language Technology at Macquarie University. http://www.clt.mq.edu.au/Events/Conferences/anlp2002/
MIT // The Algorithms Group At CSAIL The Algorithms Group, part of the Theory of Computation (TOC) group in the Computer Science and artificial intelligence Laboratory (CSAIL). People and research projects. http://theory.lcs.mit.edu/groups/algorithms.html
Extractions: at CSAIL About Research People Classes ... Contact The Algorithms Group The Algorithms Group at the Massachusetts Institute of Technology ( MIT ), is part of the Theory of Computation ( TOC ) group at the MIT's Computer Science and Artificial Intelligence Laboratory ( CSAIL ). This research group focuses upon practical and theoretical applications for Algorithms. We have faculty, students, and visitors from both the Department of Electrical Engineering and Computer Science and the Department of Mathematics Site last updated 3 August, 2005 17:55 Massachusetts Institute
Carlosweb Carlos Calderon's research combining virtual environments and artificial intelligence techniques to enhance the interactivity of a VE. http://www.staff.ncl.ac.uk/carlos.calderon/
Extractions: [Suomeksi] "Games, Computer, and People" symposium , May 19, 1999, University of Art and Design UIAH, Helsinki Official meeting, May 19, 1999, University of Art and Design UIAH, Helsinki International Joint Conference on Artificial Intelligence , Stockholm, July 31 - August 6, 1999 Networks'99 in Helsinki region, August 9 - 10, 1999
PC AI - Forth Programming Language Forth history and selected links, with a focus on artificial intelligence. http://www.pcai.com/web/ai_info/pcai_forth.html
Extractions: Forth Programming Language Overview : Charles Moore created Forth in the 1960s and 1970s to give computers real-time control over astronomical equipment. A number of Forth's features (such as its interactive style) make it a useful language for AI programming, and devoted adherents have developed Forth-based expert systems and neural networks. Functions in Forth are called "words." The programmer uses Forth's built-in words to create new ones and store them in Forth's "dictionary." In a forth program, words pass information to one another by placing data onto (and removing data from) a "stack," a software structure in which the last element in is the first element out. Using a stack in this way (Forth's unique contribution to the world of programming languages) enables Forth applications to run quickly and efficiently. Two groups of loyalists (the Forth Interest Group and the Institute for Applied Forth Research) help promote the language. Two lively books by Brodie (1984, 1987) are perhaps the best-known introductions to Forth, and an article by Sperry (1991) is a short, well-informed overview. Townsend and Feucht (1968) discuss Forth in connection with expert systems. The San Jose-based Forth Interest Group lists a number of independent developers who have build Forths for various platforms.
The AI Group At The University Of Manchester artificial intelligence IIartificial intelligence II. artificial intelligence II Introduction AI Systems and Definitions An example of intelligent action Summary http://www.cs.man.ac.uk/ai/
Extractions: Go to main content contact us help You are here: Main site School of Computer Science The AI group provides theoretically sound solutions to a range of real world problems. We are a very diverse group, with wide-ranging interests and expertise, allowing us to approach research in AI from a variety of perspectives. More information on the people that constitute the AI group is available here Fully funded PhD studentships in Machine Learning are now available.
