A Simple, Solid, and Reproducible Baseline for Bridge Bidding AI

TL;DR

This paper presents a simple yet effective baseline for bridge bidding AI that outperforms current state-of-the-art methods, using an approach that is easy to reproduce and open-source.

Contribution

The study introduces a straightforward combination of existing methods that achieves superior performance in bridge bidding against top benchmarks, providing a solid foundation for future research.

Findings

Outperforms current state-of-the-art bridge bidding systems

Uses a simple, reproducible approach with existing methods

Provides open-source code and models for the community

Abstract

Contract bridge, a cooperative game characterized by imperfect information and multi-agent dynamics, poses significant challenges and serves as a critical benchmark in artificial intelligence (AI) research. Success in this domain requires agents to effectively cooperate with their partners. This study demonstrates that an appropriate combination of existing methods can perform surprisingly well in bridge bidding against WBridge5, a leading benchmark in the bridge bidding system and a multiple-time World Computer-Bridge Championship winner. Our approach is notably simple, yet it outperforms the current state-of-the-art methodologies in this field. Furthermore, we have made our code and models publicly available as open-source software. This initiative provides a strong starting foundation for future bridge AI research, facilitating the development and verification of new strategies and advancements in the field.