TDS+: Improving Temperature Discovery Search
Abstract
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.
Cite
Text
Zhang and Müller. "TDS+: Improving Temperature Discovery Search." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9363Markdown
[Zhang and Müller. "TDS+: Improving Temperature Discovery Search." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/zhang2015aaai-tds/) doi:10.1609/AAAI.V29I1.9363BibTeX
@inproceedings{zhang2015aaai-tds,
title = {{TDS+: Improving Temperature Discovery Search}},
author = {Zhang, Yeqin and Müller, Martin},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2015},
pages = {1241-1247},
doi = {10.1609/AAAI.V29I1.9363},
url = {https://mlanthology.org/aaai/2015/zhang2015aaai-tds/}
}