Kit Library / Computer Science / Artificial Intelligence
⚡ Topic Learning KitAI Fundamentals: Adversarial Search, Probabilistic Models & Logical Agents
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AI Fundamentals: Adversarial Search, Probabilistic Models & Logical Agents
This topic introduces three core pillars of classical AI: adversarial search for competitive decision-making (Minimax, alpha-beta pruning, k-ply lookahead), probabilistic reasoning with Bayes networks, and logical agents…
- PEAS = Performance measure, Environment, Actuators, Sensors — the specification checklist for any agent.
- Adversarial search applies to two-player, turn-taking, zero-sum games like tic-tac-toe.
- Minimax alternates MAX (agent) and MIN (opponent) nodes in a game tree.
~15 min · full explanation, examples & memory tricks in the app
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