Smooth UCT Search in Computer Poker

Authors: Johannes Heinrich, David Silver

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental When applied to Kuhn and Leduc poker, Smooth UCT approached a Nash equilibrium, whereas UCT diverged. In addition, Smooth UCT outperformed UCT in Limit Texas Hold em and won 3 silver medals in the 2014 Annual Computer Poker Competition.
Researcher Affiliation Collaboration Johannes Heinrich University College London London, UK j.heinrich@cs.ucl.ac.uk David Silver Google Deep Mind London, UK davidsilver@google.com
Pseudocode Yes Algorithm 1 Self-play MCTS in extensive-form games; Algorithm 2 Smooth UCT
Open Source Code No The paper does not provide any links or explicit statements about the open-source availability of their code.
Open Datasets Yes We evaluated Smooth UCT in the Kuhn, Leduc and Limit Texas Hold em poker games. Kuhn poker [Kuhn, 1950] and Leduc Hold em [Southey et al., 2005] are small imperfect-information two-player zero-sum games...
Dataset Splits No The paper describes calibrating parameters and evaluating performance, but it does not explicitly define or specify a separate 'validation' dataset split with percentages or counts.
Hardware Specification No We trained on a modern desktop PC, using a single thread and less than 200 MB of RAM.
Software Dependencies No The paper does not specify version numbers for any software dependencies used in the experiments.
Experiment Setup Yes Smooth UCT s mixing parameter schedule (2) was manually calibrated and set to γ = 0.1, η = 0.9 and d = 0.001... In the exploration schedule (3) we set k = 0.5 and C = 24, which corresponds to half of the maximum potsize achievable in two-player LHE.