Adversarial Search in AI | Minimax, Alpha-Beta, Expectiminimax & Game-Playing Strategies Explained

Welcome to Episode 11 of our Artificial Intelligence lecture series! 🎓 In this video, we explore Adversarial Search (Game-Playing Search) – one of the most fascinating areas of AI. From chess and backgammon to modern AI strategies, you’ll learn how intelligent agents make decisions in competitive environments. 🔑 Topics Covered: The challenge of move ordering and how it affects alpha-beta pruning. Transposition tables and killer move heuristics for efficient search. Designing powerful evaluation functions in chess and other games. Problems like the horizon effect and quiescence search s…