141. Artificial Intelligence (AI) - Addison-Wesley And Benjamin Cummings Catalog artificial intelligence A Guide to Intelligent Systems, 2/E Michael Negnevitsky, School of Electrical Engineering computer science, University of Tasmania http://www.aw-bc.com/catalog/academic/course/0,1143,69987,00.html

Select a Discipline Chemistry Computer Science Economics Finance Life Science Mathematics Physics/Astronomy Statistics by Keyword by Author by Title by ISBN Advanced Search Sort by: Author Title New Edition! Available for Fall Classes! Artificial Intelligence: A Guide to Intelligent Systems, 2/E Michael Negnevitsky, / 0-321-20466-2 / Addison-Wesley New Edition! Available for Fall Classes! Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 5/E George Luger, University of New Mexico / 0-321-26318-9 / Addison-Wesley Artificial Intelligence: A Guide to Intelligent Systems Michael Negnevitsky / 0-201-71159-1 / Addison-Wesley Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 4/E George F. Luger / 0-201-64866-0 / Addison-Wesley PROLOG Programming for Artificial Intelligence, 3/E Ivan Bratko, University of Ljubljana / 0-201-40375-7 / Addison-Wesley Artificial Intelligence: Theory and Practice Thomas Dean, American Association of Artificial Intelligence / 0-8053-2547-6 / Addison-Wesley Artificial Intelligence, 3/E

142. Brown CS: Artificial Intelligence artificial intelligence at Brown University is concerned with theoretical and empirical studies is comprised of members from both the computer science and the http://www.cs.brown.edu/research/ai/

Home Search About Us News ... Research AI People Publications Comp Finance Graphics ... Industrial Relations Artificial Intelligence People Faculty Michael Black Eugene Charniak Thomas Dean Amy Greenwald Thomas Hofmann Pascal Van Hentenryck Postdocs Graduate students Undergraduate students Alumni ... Publications Major Grants IGERT Research Groups BLLIP (Brown Laboratory for Linguistic Information Processing) BLLIP is research group for the stufy of computational linguistics (or, if you prefer, Natural Language Processing). It is comprised of members from both the Computer Science and the Cognitive and Linguistic Science departments. Events Every week BLLIP group meeting, for discussion of current work in the Natural Language Processing (i.e. computational linguistics) group. Every Friday at 11am in the Cog Sci conference room (Metcalf 229?). Semiregular AI Lunch , for presentations of current and in-progress AI papers, practice talks, etc. Often on Wednesdays at noon in the conference room (CIT 506). Information on particular areas Partially observable Markov decision processes (POMDPs) Uncertainty in AI Bayesian networks, belief networks, influence diagrams ... Planning and scheduling Page Owner: Don Blaheta Last Modified: Tue Jun 4 13:46:47 2002

143. University Courses In Computer And Information Science Introductory; Algorithms; artificial intelligence; Automata Theory and Formal Models of Security (from NYU); Other Courses in computer and Information science; http://www.cis.temple.edu/courses.html

(WWW) UNIVERSITY COURSES IN COMPUTER AND INFORMATION SCIENCE. These are NOT Distance Education Courses Introductory Algorithms Artificial Intelligence Automata Theory and Formal Models of Computation ... Educational Resources for Computer Science according to SIGCSE If you are looking for Distance Education Courses you can check: Global Network Academy: Course Catalog The Yahoo list on Distance Learning Please mail suggestions to ingargiola@cis.temple.edu

144. SCMS > Computer Science: BCMS Programmes a study of the problems and techniques of artificial intelligence with more psychology in addition to the School s core of computer science, mathematics, and http://www.cs.waikato.ac.nz/genquery.php?linklist=CS&linktype=folder&linkname=BC

145. Bayesian Artificial Intelligence (Chapman And Hall/CRC Computer Science And Data Bayesian artificial intelligence (Chapman and Hall/CRC computer science and Data Analysis). Bayesian artificial intelligence (Chapman http://www.sciencesbookreview.com/Bayesian_Artificial_Intelligence_Chapman_and_H

Bayesian Artificial Intelligence (Chapman and Hall/CRC Computer Science and Data Analysis) Bayesian Artificial Intelligence (Chapman and Hall/CRC Computer Science and Data Analysis) by Authors: Kevin B. Korb , Ann E. Nicholson Released: September, 2003 ISBN: 1584883871 Hardcover Sales Rank: List price: Our price: You save: Book > Bayesian Artificial Intelligence (Chapman and Hall/CRC Computer Science and Data Analysis) > Customer Reviews: Average Customer Rating: Bayesian Artificial Intelligence (Chapman and Hall/CRC Computer Science and Data Analysis) > Customer Review #1: Bayesian Networks for Undergrads and Practicioners Despite its name "Bayesian Artificial Intelligence" covers Bayesian network (BN) techniques only. Other Bayesian techniques useful for AI are not treated. The content is divided in three main sections: (1) The basics of probabilistic reasoning with BNs, (2) Causal discovery (finding BNs from data), and (3) "Knowledge engineering".

146. Computer Science Courses translation, program execution time, computer networks, parallel computation, computability and artificial intelligence. Impact of computer science on modern http://www.cs.trinity.edu/About/The_Courses/catalog/catalog.html

COMPUTER SCIENCE MAURICE L. EGGEN, Ph.D., Associate Professor THOMAS E. HICKS, Ed.D., Associate Professor JOHN E. HOWLAND, Ph.D., Professor AARON H. KONSTAM, Ph.D., Professor J. PAUL MYERS, JR., Ph.D., Associate Professor GERALD N. PITTS, Ph.D., Professor; Chair RONALD E. PRATHER, Ph.D., Caruth Distinguished Professor of Computer Science The Major The requirements for the degree of Bachelor of Science with a major in Computer Science are as follows: I. The common curriculum II. Departmental requirements: 42 semester hours of computer science including: A. The undergraduate core: CSCI 311, CSCI 312, CSCI 314, CSCI 316, CSCI 320, CSCI 324, CSCI 325, CSCI 364, CSCI 374 B. One course chosen from each of the following areas: SYSTEMS: CSCI 341, CSCI 342, CSCI 346, CSCI 349 APPLICATIONS: CSCI 351, CSCI 353, CSCI 357, CSCI 358, CSCI 373 THEORY: CSCI 361, CSCI 363, CSCI 365, CSCI 367, CSCI 368 C. Senior Thesis (CSCI 378) or Senior Software Project (CSCI 376). D. Sufficient computer science electives to total 42 semester hours. III. Additional requirements include MATH 411 and two of the following courses: MATH 312, MATH 320, MATH 323, PHIL 310.

147. Computer Science And Artificial Intelligence (MRes) The MRes is unlike traditional taught Masters degrees in that it is designed for graduates with computer science and artificial intelligence degrees who have http://www.sussex.ac.uk/informatics/1-3-2-2-7-7.html

home Teaching Informatics degrees Postgraduate degrees ... Masters programmes CSAI entry requirements CSAI full time CSAI part time Computer Science and Artificial Intelligence (MRes) Overview The MRes is unlike traditional taught Masters degrees in that it is designed for graduates with Computer Science and Artificial Intelligence degrees who have already decided that they want a career in research. Students are attached to one of our successful research groups and receive personal tutoring and supervision in Evolutionary and Adaptive Systems, Neural Networks, Computer Vision, Natural Language Processing, Human Centred Computing Systems, or Distributed Programming Languages. Programme Objectives The emphasis is on research training and four of the six taught modules involve skill-based learning while the remaining two modules involve learning specialised knowledge associated with the students chosen area of research. This kind of research training has the following main advantages: for research in academia, the MRes qualification will provide a valuable competitive advantage in applying for DPhil or PhD places for industrial research, the MRes training will provide both vocational skills and expertise in carrying out a substantial research project.

148. Artificial Intelligence for Computing Machinery (ACM) Special Interest Group on artificial intelligence from 197779, and served as Executive Editor of Cognitive science from 1983-86 http://www.cs.washington.edu/homes/lazowska/cra/ai.html

Artificial Intelligence: Realizing the Ultimate Promises of Computing David L. Waltz Vice President, Computer Science Research NEC Research Institute Bringing Common Sense, Expert Knowledge, and Superhuman Reasoning to Computers Artificial Intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades. Although there are some fairly pure applications of AI such as industrial robots, or the Intellipath TM Autonomous vehicles: A DARPA-funded onboard computer system from Carnegie Mellon University drove a van all but 52 of the 2849 miles from Washington, DC to San Diego, averaging 63 miles per hour day and night, rain or shine; Computer chess: Deep Blue , a chess computer built by IBM researchers, defeated world champion Gary Kasparov in a landmark performance; Mathematical theorem proving: A computer system at Argonne National Laboratories proved a long-standing mathematical conjecture about algebra using a method that would be considered creative if done by humans;

149. Research Group On Computer Vision And Artificial Intelligence Translate this page http://iamwww.unibe.ch/~fkiwww/

150. U Of Rochester CS Research artificial intelligence. Neural Models of Behavior; Center for Visual science (CVS Architecture, RunTime, and Compiler Integration for High-Performance Computing; http://www.cs.rochester.edu/research/

Home directions news Department ... related depts. URCS Research In this page: AI Systems Theory See also: Technical Reports Seminars/Talks In-progress Ph.D. Dissertations Undergraduate Research Projects ... URCS Facilities Artificial Intelligence Symbolic AI, Natural Language, and Knowledge Representation Research Overview Conversational Interaction and Spoken Dialogue Research Group TRIPS: The Rochester Interactive Planning System The TRAINS Project: Natural language dialogue and interactive planning ... Uncertain Reasoning Vision, Natural Computation, and Robotics Research Overview Resource for the Study of Neural Models of Behavior Center for Visual Science (CVS) Behavioral Effects of Varying Eye, Head, and Hand Temporal Coordination Sequences in a Natural Task ... Augmented Reality Control of robots through Differential Visual Feedback (DVFB) Appearance based visual simulation of articulated agents: Simulated Actions Visual space learning, planning and robot control: Perceptual Actions Motion Detection and Recognition Object Recognition Scale decomposition of the information content in images. ... Boundary Extraction by Lineal Feature Growing Systems Research Overview ARCH: Architecture, Run-Time, and Compiler Integration for High-Performance Computing

151. AI At Victoria University artificial intelligence at Victoria. courses at Victoria. Comp423, Intelligent agents (1/3, 2004). Comp424, Neural systems (not in 2004). computer vision. http://www.mcs.vuw.ac.nz/research/ai/

Artificial Intelligence at Victoria courses at Victoria Introduction to AI Machine Learning (2/3, 2004) Data mining, neural nets, and genetic programming (2/3, 2004) Intelligent agents (1/3, 2004) Neural systems (not in 2004) Complex adaptive systems (by arrangement only) post-graduate students Richard Mansfield (PhD student with Marcus) theoretical biology: competition between species Phillip Boyle (PhD student with Marcus) evolving autonomous agents Tim Field - MSc with Marcus: completed 2004 robotics Jerome Dolman (MSc with Marcus) Exploring Mechanisms of Neural Development through Parameterised Search Huayang 'Jason' Xie (MSc student with Pondy and Mengjie) speech recognition Mukhlis Matti (MSc student with Pondy) clustering algorithms Will Smart (MSc student with Mengjie) genetic programming staff Peter Andreae reinforcement learning clustering Marcus Frean machine learning complex adaptive systems theoretical biology Mengjie Zhang data mining machine learning genetic programming neural networks computer vision Xiaoying Gao (Sharon) information extraction from the web knowledge-based systems machine learning Tony Vignaux Bayesian methods forensic evidence

152. The 2003 International MultiConference Conference on Imaging science, Systems, and 03 The 2003 International Conference on artificial intelligence. 2003 International Conference on Internet Computing. http://www.ashland.edu/~iajwa/conferences/

CALL FOR PAPERS The 2004 International Multiconference in Computer Science and Computer Engineering (18 Joint International Conferences) Monte Carlo Resort, Las Vegas, Nevada, USA June 21-24, 2004 http://www.world-academy-of-science.org/IMCSE2004 Below is the site for Monte Carlo Resort, Las Vegas, Nevada, USA June 23 - 26, 2003 Home Contact Committee Conference Keynote ... PDPTA'03 The 2003 International Conference on Parallel and Distributed Processing Techniques and Applications CISST'03 The 2003 International Conference on Imaging Science, Systems, and Technology IC-AI'03 The 2003 International Conference on Artificial Intelligence IC'03 The 2003 International Conference on Internet Computing MLMTA'03 The 2003 International Conference on Machine Learning; Models, Technologies and Applications METMBS'03 The 2003 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences CIC'03 The 2003 International Conference on Communications in Computing ERSA'03 The 2003 International Conference on Engineering of Reconfigurable Systems and Algorithms VLSI'03 The 2003 International Conference on VLSI IKE'03 The 2003 International Conference on Information and Knowledge Engineering ICWN'03 The 2003 International Conference on Wireless Networks SERP'03 The 2003 International Conference on Software Engineering Research and Practice SAM'03 The 2003 International Conference on Security and Management ESA'03 The 2003 International Conference on Embedded Systems and Applications

153. MIT Artificial Intelligence Lab The artificial intelligence Laboratory has been an active entity at MIT in one form or another since at least 1959. Our goal is http://www.ai.mit.edu/

On July 1, 2003, the MIT AI Lab and LCS merged to become MIT CSAIL The Artificial Intelligence Laboratory has been an active entity at MIT in one form or another since at least 1959. Our goal is to understand the nature of intelligence and to engineer systems that exhibit intelligence. We are an interdisciplinary laboratory of over 200 people that spans several academic departments and has active projects ongoing with members of every academic school at MIT. Our intellectual goal is to understand how the human mind works. We believe that vision, robotics, and language are the keys to understanding intelligence, and as such our laboratory is much more heavily biased in these directions than many other Artificial Intelligence laboratories [Academics] [AI Lab Home Page] [Contact Us] [Events] ... [Visiting the Lab] MIT Artificial Intelligence Laboratory, 200 (545) Technology Square, MIT Building NE43, Cambridge, MA 02139 USA, Tel: (617) 253-6218 webmaster: annika

154. SCHOOL OF COMPUTER SCIENCE/Carnegie Mellon University Wing Professor CSD, and new head of the computer science Department (CSD) tells why she is known as Students from the School of computer science, Take a tour of SCS http://www.cs.cmu.edu/

Admissions Areas Faculty Divisions ... Intranet Search SCS News and Events: Features: Jeannette M. Wing, Professor CSD, and new head of the Computer Science Department (CSD) tells why she is known as Dragon Lady in this new interview by Women@SCS. Wing is highly regarded for her outstanding contributions in research, teaching, and administrative service to the college. Full interview New director Todd Mowry takes the reins from Mahadev Satyanarayanan (Satya) at Intel Research Pittsburgh Lab going strong after two years of innovative research projects More information Celebrating Transitions: In Honor of James Morris, Randal Bryant, Jeannette Wing and Chuck Thorpe Friday, June 4, 3:30 p.m., The Perlis Atrium Newell-Simon Hall More News in: Carnegie Mellon News Carnegie Mellon Magazine SCS Interview Series: Guess who you might see on the Allegheny River early in the morning?

155. Berkeley CS Division Home Page The computer science Division. computer science Division Office. University of California Department of Electrical Engineering and computer sciences. University of California, Berkeley http://www.cs.berkeley.edu/

The Computer Science Division Computer Science Division Office University of California, Berkeley 387 Soda Hall #1776 Berkeley, CA 94720-1776 CS Brochure (pdf) 30th Anniversary Celebration View the Webcast Berkeley EECS Annual Research Symposium (BEARS) View the Webcast In the News: CITRIS Center for Information Technology Research in the Interest of Society People Rosters and Directories Faculty Addresses Photos Visiting Faculty Scholars Administrative Staff Alumni Home Pages ... E-mail Aliases Research Areas Projects Technical Reports Creating CS Tech Reports ... FTP archive Class and Student Info Classes Organizations Newsgroups CS Graduate Student Roster ... UCSEE Student Resume Service Information for: Prospective EECS Students Incoming Students Undergraduates Graduates CS Resource Guide Staff Directory Administrative Services Academic Student Services Emergency Information Seminars and Conferences Seminars and Colloquia Joint Colloquium Conferences EECS Event Calendar Administration Administrative Staff and Services Policies Forms Information for EECS Faculty ... EECS Administration Soda Hall Information Directions to Soda CS Roster Resource Guide Room Reservations ... The Software Warehouse (SWW) Service E-mail Aliases UC Berkeley Dialup Services Setting up a CS Home Page How To ... UC Berkeley Department of Electrical Engineering and Computer Sciences University of California, Berkeley

156. Networked Computer Science Technical Reference Library Networked computer science Technical Reference Library NCSTRL (Networked computer science Technical Reference Library) is a collection of legacy and current technical reports from over 100 http://rdre1.inktomi.com/click?u=http://www.ncstrl.org/&y=02DD48352F948907&a

157. Research Index Logo, Department of computer science, Thomas M. Siebel Center for computer science, 201 N. Goodwin, Urbana, IL 618012302. The Department http://www.cs.uiuc.edu/research/

Research Introduction Areas PhD Thesis Research Undergraduate Research Opportunities ... Summary of Research Department of Computer Science, Thomas M. Siebel Center for Computer Science, 201 N. Goodwin, Urbana, IL 61801-2302. The Department is part of the College of Engineering at the University of Illinois at Urbana-Champaign Contact webmaster@cs.uiuc.edu with questions or comments on this page or academic@cs.uiuc.edu with academic questions. This site was created 12/01/01.

158. AILab, University Of Zurich artificial intelligence Laboratory Department of Information Technology University of Zürich. Director Prof. Dr. Rolf Pfeifer. Department http://www.ifi.unizh.ch/ailab/

159. AIRVL, University Of Minnesota Intelligent Transportation Systems; MinDART Minnesota Distributed Autonomous Robotics University of Minnesota Department of computer science and Engineering. http://www.cs.umn.edu/Research/airvl/

Room B22 Walter Engineering and Science Library 117 Pleasant Street SE Minneapolis, MN 55455 [AIRVL Home] [ People Research Facilities People Overview Faculty Graduate Students Undergraduate Students ... Visitors Research Overview Connectionist Learning for Robot Control Distributed Robotics Using Reconfigurable Robots Human Activity Monitoring ... Vehicle Navigation and Localization Facilities Overview Lego-based Mini Robots Eric the Red MVRT, Minnesota Robotics Visual Tracker Others to be added... Department of Computer Science and Engineering Comments to: Ashutosh Jaiswal The University of Minnesota is an equal opportunity educator and employer. document.write( "Last updated "+ document.lastModified ); //end hiding contents >

160. DTAI - Machine Learning Within the field of artificial intelligence, machine learning occupies a as there can be no intelligence unless it as that offered by computational logic, both http://www.cs.kuleuven.ac.be/~ml/index-E.shtml

ML DTAI Dept. of Computer Science Faculty of Engineering ... K.U.Leuven DTAI Machine Learning [NEDERLANDS] ENGLISH Machine learning ( ML ) is concerned with building agents that improve their performance on specific tasks by accumulating and processing experience. Within the field of artificial intelligence, machine learning occupies a central position as there can be no intelligence unless it is capable of learning. General information: Members of the research group Publications Available systems and data sets Research, education and relevant links Research topics: Data Mining The aim of data mining is to find regularities in (possibly large) sets of data. These regularities can be used either for predictive purposes, or for descriptive purposes. As an example of the former, if the data is about patients, their symptoms and diagnosis, one can combine the symptoms of a new patient with the induced regularities to propose a diagnosis. As an example of the latter, in the same domain, an induced regularity describes a piece of scientific knowledge. If previously unknown to the medical doctors, it constitutes a piece of new knowledge which enhances the understanding of the domain. Inductive Logic Programming Classical data mining is suitable for learning patterns from data with a simple structure (typically a single relation where each tuple describes an example). However, the emphasis of our research lies on the development of algorithms that are able to induce regularities in structured domains (e.g. in biochemistry). This requires the use of an expressive representation language such as that offered by computational logic, both to describe the complex data used for learning and to express the patterns that are learnt. This has lead to the field of inductive logic programming, in which our group occupies a leading position.

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