---
title: "Smooth UCT Search in Computer Poker"
authors:
  - "Johannes Heinrich"
  - "David Silver"
doi: ""
url: "https://ijcai.org/proceedings/2015/84"
pdf: "https://ijcai.org/proceedings/2015/0084.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "554-559"
track: "Main Track"
keywords:
---

# Smooth UCT Search in Computer Poker

Johannes Heinrich, David Silver

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 554-559.

## Abstract

Self-play Monte Carlo Tree Search (MCTS) has been successful in many perfect-information two-player games. Although these methods have been extended to imperfect-information games, so far they have not achieved the same level of practical success or theoretical convergence guarantees as competing methods. In this paper we introduce Smooth UCT, a variant of the established Upper Confidence Bounds Applied to Trees (UCT) algorithm. Smooth UCT agents mix in their average policy during self-play and the resulting planning process resembles game-theoretic fictitious play. 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.