PPT-Games and adversarial search

Author : briana-ranney | Published Date : 2017-09-22

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. etc. Convnets. (optimize weights to predict bus). bus. Convnets. (optimize input to predict ostrich). ostrich. Work on Adversarial examples by . Goodfellow. et al. , . Szegedy. et. al., etc.. Generative Adversarial Networks (GAN) [. 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.. Statistical Relational AI. Daniel Lowd. University of Oregon. Outline. Why do we need adversarial modeling?. Because of the dream of AI. Because of current reality. Because of possible dangers. Our initial approach and results. Chapter 6. Section 1 – 4. Outline. Optimal decisions. α-β pruning. Imperfect, real-time decisions. Games vs. search problems. "Unpredictable" opponent . . specifying a move for every possible opponent . Nets. İlke Çuğu 1881739. NIPS 2014 . Ian. . Goodfellow. et al.. At a . glance. (. http://www.kdnuggets.com/2017/01/generative-adversarial-networks-hot-topic-machine-learning.html. ). Idea. . Behind. (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. Adversarial examples. Ostrich!. Adversarial examples. Ostrich!. Intriguing properties of neural networks. . Christian . Szegedy. , . Wojciech. . Zaremba. , Ilya . Sutskever. , Joan Bruna, . Dumitru. CS344 Seminar Presentation. 1. Group 4. Team Members. (In the lexicographic order of roll number):. Adhip. Agarwal (07005009). Raman Sharma (07005010). Gaurav Malpani (07005011). Sumit. . Somani. (07005012). 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." . for . edge detection. Z. Zeng Y.K. Yu, K.H. Wong. In . IEEE iciev2018, International Conference on Informatics, Electronics & Vision '. June,kitakyushu. exhibition center, japan, 25~29, 2018. (. Games and adversarial s 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 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 . 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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