# The αμ Search Algorithm for the Game of Bridge

arXiv: https://arxiv.org/abs/1911.07960 · HTML: https://mlsanity.com/paper/1911.07960/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Nov 2019.

## Built on by (most cited first, 6 of 6)

- [Optimizing αμ](https://mlsanity.com/paper/2101.12639/) (2021)
- [Mixture of Public and Private Distributions in Imperfect Information Games](https://mlsanity.com/paper/2405.14346/) (2024)
- [On the Power of Refined Skat Selection](https://mlsanity.com/paper/2104.02997/) (2021)
- [Knowledge-Based Paranoia Search in Trick-Taking](https://mlsanity.com/paper/2104.05423/) (2021)
- [Perfect Information Monte Carlo with Postponing Reasoning](https://mlsanity.com/paper/2408.02380/) (2024)
- [Outer-Learning Framework for Playing Multi-Player Trick-Taking Card Games: A Case Study in Skat](https://mlsanity.com/paper/2512.15435/) (2025)

## Abstract (arXiv)

αμ is an anytime heuristic search algorithm for incomplete information games that assumes perfect information for the opponents. αμ addresses the strategy fusion and non-locality problems encountered by Perfect Information Monte Carlo sampling. In this paper αμ is applied to the game of Bridge.