TDS+: Improving Temperature Discovery Search
Full Text: 9554-44179-1-PB.pdf
Temperature Discovery Search (TDS) is a forward search method for computing or approximating the temperature of a combinatorial game. Temperature and mean are important concepts in combinatorial game theory, which can be used to develop efficient algorithms for playing well in a sum of subgames. A new algorithm TDS+ with five enhancements of TDS is developed, which greatly speeds up both exact and approximate versions of TDS. Means and temperatures can be computed faster, and fixed-time approximations which are important for practical play can be computed with higher accuracy than before.
Citation
Y. Zhang, M. Müller. "TDS+: Improving Temperature Discovery Search". National Conference on Artificial Intelligence (AAAI), (ed: Blai Bonet, Sven Koenig), pp 1241-1247, January 2015.| Keywords: | Temperature Discovery Search, TDS+, combinatorial game theory, sum games, game tree search, Amazons |
| Category: | In Conference |
| Web Links: | AAAI |
BibTeX
@incollection{Zhang+Müller:AAAI15,
author = {Yeqin Zhang and Martin Müller},
title = {TDS+: Improving Temperature Discovery Search},
Editor = {Blai Bonet, Sven Koenig},
Pages = {1241-1247},
booktitle = {National Conference on Artificial Intelligence (AAAI)},
year = 2015,
}Last Updated: June 30, 2020Submitted by Sabina P
