PPT-Games and adversarial search

Author : tatiana-dople | Published Date : 2017-03-16

Chapter 5 World Champion chess player Garry Kasparov is defeated by IBMs Deep Blue chessplaying computer in a sixgame match in May 1997 link Telegraph Group

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Games and adversarial search: Transcript


Chapter 5 World Champion chess player Garry Kasparov is defeated by IBMs Deep Blue chessplaying computer in a sixgame match in May 1997 link Telegraph Group Unlimited 1997. INQUISITORIAL. -Judge can ask the accused questions. -Accused must answer questions from lawyers as well as the judge. -Accused may not be presumed innocent and the burden of proof may be on them to prove their innocence. Search. (game playing search). We have experience in search where we assume that we are the only intelligent . entity and . we have explicit control over the “world”.. Let us . consider what happens when we relax those assumptions.. Dr. Jey Veerasamy. jeyv@utdallas.edu. July 31. st. – August 23. rd. 9:30 am to 12 noon. 1. Memory game. 2. Minesweeper. 3. C. onnect4. 4. Deal or no deal. 5. Bouncing ball. 6. Sudoku. 7. (Chapter 5). World Champion chess player Garry Kasparov . is . defeated by IBM’s Deep Blue chess-playing computer in a . six-game . match in May, . 1997. (. link. ). © Telegraph Group . Unlimited 1997. (Chapter 5). World Champion chess player Garry Kasparov . is . defeated by IBM’s Deep Blue chess-playing computer in a . six-game . match in May, . 1997. (. link. ). © Telegraph Group . Unlimited 1997. We have experience in search where we assume that we are the only intelligent entity and we have explicit control over the “world”.. Let us consider what happens when we relax those assumptions. We have an . Adversarial examples. Ostrich!. Adversarial examples. Ostrich!. Intriguing properties of neural networks. . Christian . Szegedy. , . Wojciech. . Zaremba. , Ilya . Sutskever. , Joan Bruna, . Dumitru. ML Reading . Group. Xiao Lin. Jul. 22 2015. I. . Goodfellow. , J. . Pouget-Abadie. , M. Mirza, B. Xu, D. . Warde. -Farley, S. . Ozair. , A. . Courville. and Y. . Bengio. . . "Generative adversarial nets." . earch. Why study games?. Games are a traditional hallmark of intelligence. Games are easy to formalize. Games can be a good model of real-world competitive activities. Military confrontations, negotiation, auctions, etc.. earch. Why study games?. Games can be a good model of many competitive activities. Military confrontations, negotiation, auctions, …. Games are a traditional hallmark of intelligence. Contrarian viewpoint (textbook): . AIMA . Chapter. 5.1 – 5.5. AI vs. Human Players: the State of the Art. 4. To Be Updated next year!. Deterministic. Games . in. Practice. Checkers: . Chinook . ended 40-year-reign of human world champion Marion Tinsley in 1994. Used a . Mini-max, Cutting Off Search. CS. 171. , . Summer 1. . Quarter, 2019. Introduction to Artificial Intelligence. Prof. . Richard Lathrop. Read Beforehand:. R&N 5.1, 5.2, 5.4. Outline. Computer . programs that play 2-player . Dr. Alex Vakanski. Lecture 6. GANs for Adversarial Machine Learning. Lecture Outline. Mohamed Hassan presentation. Introduction to Generative Adversarial Networks (GANs). Jeffrey Wyrick presentation. Attacks. Haotian Wang. Ph.D. . . Student. University of Idaho. Computer Science. Outline. Introduction. Defense . a. gainst . Adversarial Attack Methods. Gradient Masking/Obfuscation. Robust Optimization.

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