
This episode explores adversarial search in game-playing AI, covering game formulation, minimax, game trees, evaluation functions, alpha-beta pruning and expectimax. Disclosure: This episode was generated using NotebookLM by uploading Professor Chris Callison-Burch's lecture notes and slides.
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CIS 5210 - Module 8 - Reinforcement Learning

CIS 5210 - Module 7 - Markov Decision Processes

CIS 5210 - Module 6 - Knowledge-Based Agents and Logical Reasoning

CIS 5210 - Module 5 - CSPs
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