ML Anthology

Temperature Discovery Search

Martin Müller, Markus Enzenberger, Jonathan Schaeffer
AAAI 2004 pp. 658-663
/aaai/2004/muller2004aaai-temperature/

Abstract

Temperature Discovery Search (TDS) is a new minimaxbased game tree search method designed to compute or approximate the temperature of a combinatorial game. TDS is based on the concept of an enriched environment, where a combinatorial game G is embedded in an environment consisting of a large set of simple games of decreasing temperature. Optimal play starts in the environment, but eventually must switch to G. TDS finds the temperature of G by determining when this switch must happen. Both exact and heuristic versions of TDS are described and evaluated experimentally. In experiments with sum games in Amazons, TDS outperforms an αβ searcher.

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Cite

Text

Müller et al. "Temperature Discovery Search." AAAI Conference on Artificial Intelligence, 2004.

Markdown

[Müller et al. "Temperature Discovery Search." AAAI Conference on Artificial Intelligence, 2004.](https://mlanthology.org/aaai/2004/muller2004aaai-temperature/)

BibTeX

@inproceedings{muller2004aaai-temperature,
  title     = {{Temperature Discovery Search}},
  author    = {Müller, Martin and Enzenberger, Markus and Schaeffer, Jonathan},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2004},
  pages     = {658-663},
  url       = {https://mlanthology.org/aaai/2004/muller2004aaai-temperature/}
}