Topic

Monte Carlo Tree Search

Latest viewpoints

AlphaGo uses Monte Carlo Tree Search for expensive test-time planning.

The speaker details how AlphaGo uses MCTS, performing many model invocations to build a search tree that balances exploration and exploitation to select optimal moves in games with small action spaces.

Francois Chaubard Monte Carlo Tree Search Source at 26:40

MCTS scaling is limited by large action spaces and real-time requirements.

The speaker explains that the MCTS approach used in AlphaGo does not scale to domains like self-driving or robotics because of large action spaces, non-deterministic environments, and the need for real-time decisions.

Francois Chaubard Monte Carlo Tree Search Source at 33:14

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