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 STYLE
Zhang, Y., & Müller, M. (2015). TDS+: Improving temperature discovery search. In Proceedings of the National Conference on Artificial Intelligence (Vol. 2, pp. 1241–1247). AI Access Foundation. https://doi.org/10.1609/aaai.v29i1.9363
Mendeley helps you to discover research relevant for your work.