Name
Abstract | ||
|---|---|---|
Phantom Go is a derivative of Go with imperfect information. It is challenging in AI field due to its great uncertainty of the hidden information and high game complexity inherited from Go. To deal with this imperfect information game with large game tree complexity, a general search framework named belief-state Monte Carlo tree search (BS-MCTS) is put forward in this paper. BS-MCTS incorporates b... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCIAIG.2017.2734067 | IEEE Transactions on Games |
Keywords | DocType | Volume |
Games,Monte Carlo methods,Phantoms,Artificial intelligence,Complexity theory,Game theory,Computational modeling | Journal | 10 |
Issue | ISSN | Citations |
2 | 2475-1502 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |