The αμ Search Algorithm for the Game of Bridge
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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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Nov 2019.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 2; 2025: 1.
6 papers.
- 2021Optimizing αμcited by 4
- 2024Mixture of Public and Private Distributions in Imperfect Information Gamescited by 1
- 2021On the Power of Refined Skat Selectioncited by 0
- 2021Knowledge-Based Paranoia Search in Trick-Takingcited by 0
- 2024Perfect Information Monte Carlo with Postponing Reasoningcited by 0
- 2025Outer-Learning Framework for Playing Multi-Player Trick-Taking Card Games: A Case Study in Skatcited by 0
- 2025Outer-Learning Framework for Playing Multi-Player Trick-Taking Card Games: A Case Study in Skat17 Dec 2025
- 2024Perfect Information Monte Carlo with Postponing Reasoning5 Aug 2024
- 2024Mixture of Public and Private Distributions in Imperfect Information Games23 May 2024
- 2021Knowledge-Based Paranoia Search in Trick-Taking7 Apr 2021
- 2021On the Power of Refined Skat Selection7 Apr 2021
- 2021Optimizing αμ29 Jan 2021