Adversarial Search (W5)

Introduction to Adversarial Search

A. Definition and purpose of adversarial search

B. Game theory and strategic decision making

Multi-Agent Environments

A. Characteristics of convenient models for AI

B. Examples of deterministic, turn-taking, two-player games

C. Focus on zero-sum games with perfect information

Solving Games

A. Challenges in calculating optimal decisions

B. Tree pruning for efficiency

C. Introduction to the Max and Min players

Minimax Algorithm

A. Normal search vs. adversarial search

B. Similarity to AND-OR search trees

C. Complete depth-first search and back-up process

D. Extending to multiplayer games with vector values

. Real-World Scenarios

A. Emergence of alliances and collaborations

B. Rationality of cooperation vs. aggression

C. Examples: Prisoner's dilemma and multi-agent planning

Coordination and Communication

A. Coordination through conventions

B. Communication and plan recognition

C. Evolution of conventions and behaviors

Emergent Behavior and Flocking

A. Examples from biological systems and animal behavior

B. Craig Reynolds' boids and emergent complexity

C. Steering behaviors and pseudocode