Abstract
We propose a general approach for encoding epistemic strategies for playing incomplete information games. A game strategy involves selecting actions in order to maximise an outcome (e.g., winning the game). In an epistemic strategy the selection of actions is based on reasoning about the knowledge of other players. We show how epistemic strategies can be encoded by supplementing a GDL-II game description with a set of epistemic rules to produce a GDL-III game that an appropriate reasoner can use to play the original GDL-II game. We prove the formal correctness of this approach and provide a practical evaluation to show its efficacy for playing the co-operative multi-player game of Hanabi. It was found that the encoded epistemic rules were able to provide players with a strategy that allowed them to play Hanabi near optimally.
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Notes
- 1.
- 2.
For the full Hanabi GDL-II encoding see: https://git.io/fhbVz.
- 3.
For the complete GDL-III information strategy encoding see: https://git.io/fhbVo.
- 4.
For the complete GDL-III implicit strategy encoding see: https://git.io/fhbVK.
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Acknowledgements
This research was supported under the Australian Research Council’s (ARC) Linkage Projects funding scheme (project number LP 180100080).
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Manuel, S., Rajaratnam, D., Thielscher, M. (2019). Encoding Epistemic Strategies for General Game Playing. In: Nayak, A., Sharma, A. (eds) PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. Lecture Notes in Computer Science(), vol 11670. Springer, Cham. https://doi.org/10.1007/978-3-030-29908-8_44
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