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CS885 Lecture 14a: Mastering the Game of Go (Presenter: Henry Chen)
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6. Search: Games, Minimax, and Alpha-Beta
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CS885 Lecture 9: Model-based RL
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Algorithms Explained – minimax and alpha-beta pruning
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CS885 Lecture 15c: Semi-Markov Decision Processes
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CS885 Lecture 8b: Bayesian and Contextual Bandits
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Lecture 18: Uninformed and Heuristic Search
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Lecture 6: Adversarial Search
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Minimax with Alpha Beta Pruning
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Mega-R3. Games, Minimax, Alpha-Beta
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CS885 Lecture 11b: Partially Observable RL
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CS885 Lecture 8a: Multi-armed bandits
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Game Playing 1 - Minimax, Alpha-beta Pruning | Stanford CS221: AI (Autumn 2019)
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The Professor Who Taught People How To Think (1962)
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CS885 Lecture 12: Deep Recurrent Q-Networks
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4. Search: Depth-First, Hill Climbing, Beam
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CS885 Lecture17c: Inverse Reinforcement Learning
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Artificial Intelligence - 5.1 - Adversarial search and games, Game theory
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Simple Explanation of the Minimax Algorithm with Alpha-Beta Pruning with Connect 4
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