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Adversarial Search and Game Theory
Introduction to Adversarial Search
Fully observable and deterministic vs. partially observable or non-deterministic environments
Importance of percepts in stochastic environments
Game Theory Overview
Optimizing agent performance
Strategic decision-making
Mathematical models of conflict and cooperation
Multi-Agent Environments
Convenient models for AI
Deterministic, turn-taking, and two-player games
Examples of zero-sum games
Coordination and Communication
Planning in multi-agent environments
Emergent patterns of behavior and steering behaviors
Biological and Artificial Examples
Flocking behaviors in animals and boids simulation
Emergent complexity and steering behaviors
Strandbeest and Emergence
Theo Jansen's Strandbeest
Emergent patterns of behavior and steering behaviors
Solving Games
Challenges in calculating optimal decisions
Efficiency and pruning techniques
Introduction to Max and Min players
Minimax Algorithm
Normal search vs. adversarial search
Consideration of opponent's moves
Similarity to AND-OR search trees
Multiplayer Games
Replacing single values with vectors
Handling games with more than two players
Real-World Applications
Prisoner's dilemma and rational decision-making
Emergence of alliances and collaboration
AND-OR Search Trees
Structure and components of AND-OR search trees
Vacuum cleaner world example
Adversarial Search and Game Theory