Adversarial Search

Extend classical search to adversarial domains, to build agents that make good decisions without any human intervention—such as the DeepMind AlphaGo agent.

Search in multi-agent domains, using the Minimax theorem to solve adversarial problems and build agents that make better decisions than humans.

Some of the limitations of minimax search and introduces optimizations & changes that make it practical in more complex domains.

Build agents that make good decisions without any human intervention—such as the DeepMind AlphaGo agent.

Extensions to minimax search to support more than two players and non-deterministic domains.

Introduce Monte Carlo Tree Search, a highly-successful search technique in game domains, along with a reading list for other advanced adversarial search topics.