BigEggStudy/UC-Berkeley-CS-188-Artificial-Intelligence

Covers core AI algorithms including uninformed search (DFS, BFS, UCS), informed search with A* and heuristics, constraint satisfaction problems, adversarial search with minimax and alpha-beta pruning, Markov decision processes, and reinforcement learning including Q-learning. Implements practical agent-based solutions in Python, with search agents navigating grid-based environments and game-playing agents using adversarial techniques. Complements Berkeley's edX course materials with quiz problems spanning search theory, CSP solving strategies, and learning algorithms.

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