Monte-Carlo Tree Search Solver

By Mark H. M. Winands, Yngvi Björnsson, Jahn-Takeshi Saito. 2008

116 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Sociology and Political Science, Game & Decision Theory, Algorithms & Complexity

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Marwin H. S. Segler
2. Ryan B. Hayward
3. Edward Jack Powley
4. Cameron Browne
5. Simon M. M. Lucas
6. Simon Colton
7. Peter I. Cowling
8. Mike Preuss

In Economics and Econometrics

1. Ryan B. Hayward
2. Edward Jack Powley
3. Cameron Browne
4. Simon M. M. Lucas
5. Simon Colton
6. Peter I. Cowling
7. Mike Preuss
8. Spyridon Samothrakis

In Sociology and Political Science

1. Julian Togelius

In Game & Decision Theory

1. Ryan B. Hayward
2. Edward Jack Powley
3. Cameron Browne
4. Simon M. M. Lucas
5. Simon Colton
6. Peter I. Cowling
7. Spyridon Samothrakis
8. Diego Perez Liebana

In Algorithms & Complexity

1. Mike Preuss
2. Mark P. Waller
3. Marwin H. S. Segler

Citations in the corpus

• Planning chemical syntheses with deep neural networks and symbolic AI (2017, background): “[44] Non-terminal states are subjected to a rollout, where actions are sampled from the rollout network recursively, until the state has been deconstructed into building blocks or a maximal depth is reached.”
• Monte Carlo Tree Search in Hex (2010, background): “However, in our tests, MoHex showed no strength gain from such patterns.”
• A Survey of Monte Carlo Tree Search Methods (2012, background): “Section 4.8.9 discusses this in more detail.”