Information capture and reuse strategies in Monte Carlo Tree Search, with applications to games of hidden information

, &
Artificial Intelligence 217 (C):92-116 (2014)
  Copy   BIBTEX

Abstract

This article has no associated abstract. (fix it)

Categories

Keywords

Reprint years

DOI

10.1016/j.artint.2014.08.002

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 93,031

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

My notes

Similar books and articles

Monte Carlo tree search in Kriegspiel.Paolo Ciancarini & Gian Piero Favini - 2010 - Artificial Intelligence 174 (11):670-684.
Monte-Carlo tree search and rapid action value estimation in computer Go.Sylvain Gelly & David Silver - 2011 - Artificial Intelligence 175 (11):1856-1875.
Temporal logic explanations for dynamic decision systems using anchors and Monte Carlo Tree Search.Tzu-Yi Chiu, Jerome Le Ny & Jean-Pierre David - 2023 - Artificial Intelligence 318 (C):103897.
Search in games with incomplete information: a case study using Bridge card play.Ian Frank & David Basin - 1998 - Artificial Intelligence 100 (1-2):87-123.
A Theory of Heuristic Information in Game-tree Search.Chun-Hung Tzeng - 1988 - Springer.
Efficient exhaustive generation of functional programs using monte-carlo search with iterative deepening.Susumu Katayama - 2008 - In Tu-Bao Ho & Zhi-Hua Zhou (eds.), Pricai 2008: Trends in Artificial Intelligence. Springer. pp. 199--210.
Limited lookahead in imperfect-information games.Christian Kroer & Tuomas Sandholm - 2020 - Artificial Intelligence 283 (C):103218.
Robust Monte Carlo localization for mobile robots.Sebastian Thrun, Dieter Fox, Wolfram Burgard & Frank Dellaert - 2001 - Artificial Intelligence 128 (1-2):99-141.
Sequential Monte Carlo in reachability heuristics for probabilistic planning.Daniel Bryce, Subbarao Kambhampati & David E. Smith - 2008 - Artificial Intelligence 172 (6-7):685-715.
Speeding up many-objective optimization by Monte Carlo approximations.Karl Bringmann, Tobias Friedrich, Christian Igel & Thomas Voß - 2013 - Artificial Intelligence 204 (C):22-29.

Analytics

Added to PP
2020-12-22

Downloads
7 (#1,411,895)

6 months
5 (#711,233)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

Depth-first iterative-deepening.Richard E. Korf - 1985 - Artificial Intelligence 27 (1):97-109.
An analysis of alpha-beta pruning.Donald E. Knuth & Ronald W. Moore - 1975 - Artificial Intelligence 6 (4):293-326.
Proof-number search.L. Victor Allis, Maarten van der Meulen & H. Jaap van den Herik - 1994 - Artificial Intelligence 66 (1):91-124.
Multi-player alpha-beta pruning.Richard E. Korf - 1991 - Artificial Intelligence 48 (1):99-111.

View all 7 references / Add more references