Patrick+Winston

an American computer scientist and professor of Artificial Intelligence at MIT. His book //Artificial Intelligence// covers the broad range of AI-Issues, including Search, Alpha-Beta and Learning. Winston is also author of various books on Programming Languages, such as Java, Smalltalk, C, C++ and Lisp. toc =Selected Publications=
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 * [[image:how-to-speak-patrick-winston.jpg link="http://sixminutes.dlugan.com/2008/03/24/speaking-tips-patrick-henry-winston-speak/"]] ||~   || **Patrick Henry Winston**,
 * Patrick Winston  ||~   ||^  ||
 * Patrick Winston  ||~   ||^  ||
 * Azriel Rosenfeld, Jerome A. Feldman, Laveen N. Kanal, Patrick H. Winston (**1977**). //AI and Pattern Recognition//. [|IJCAI 1977]
 * Patrick Winston (**1978**). //Dealing with Adversaries//. Personal Computing, Vol. 2, No. 11, pp. 30, November 1978 » Alpha-Beta
 * Ryszard Michalski, Patrick Winston (**1986**). //Variable Precision Logic//. Artificial Intelligence, Vol. 29, pp. 121-146, [|pdf]
 * Patrick Winston (**1992**) //[|Artificial Intelligence].// (third Edition)
 * Patrick Winston (**1995**). //[|On To C++]//
 * Patrick Winston (**2001**). //[|On To Java]//.

=External Links= > media type="youtube" key="STjW3eH0Cik" > media type="youtube" key="q0pm3BrIUFo"
 * [|Patrick Henry Winston Homepage]
 * [|Lecture Videos | Artificial Intelligence | Electrical Engineering and Computer Science | MIT OpenCourseWare], MIT 6.034 Artificial Intelligence, by Patrick Winston, Fall 2010, [|YouTube] Videos
 * 1) [|Introduction and Scope]
 * 2) [|Reasoning: Goal Trees and Problem Solving]
 * 3) [|Reasoning: Goal Trees and Rule-Based Expert Systems]
 * 4) [|Search: Depth-First, Hill Climbing, Beam]
 * 5) [|Search: Optimal, Branch and Bound, A*]
 * 6) Search: Games, Minimax, and Alpha-Beta
 * 1) [|Constraints: Interpreting Line Drawings]
 * 2) [|Constraints: Search, Domain Reduction]
 * 3) [|Constraints: Visual Object Recognition]
 * 4) [|Introduction to Learning, Nearest Neighbors]
 * 5) [|Learning: Identification Trees, Disorder]
 * 6) Learning: Neural Nets, Back Propagation
 * 1) [|Learning: Genetic Algorithms]
 * 2) [|Learning: Sparse Spaces, Phonology]
 * 3) [|Learning: Near Misses, Felicity Conditions]
 * 4) [|Learning: Support Vector Machines]
 * 5) [|Learning: Boosting]
 * 6) [|Representations: Classes, Trajectories, Transitions]
 * 7) [|Architectures: GPS, SOAR, Subsumption, Society of Mind]
 * 8) AI business, not available
 * 9) [|Probabilistic Inference I]
 * 10) [|Probabilistic Inference II]
 * 11) [|Model Merging, Cross-Modal Coupling, Course Summary]

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