Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/80775
Title: | Collaborative agent gameplay in the Pandemic board game |
Authors: | Sfikas, Konstantinos Liapis, Antonios |
Keywords: | Games -- Design Artificial intelligence Board games |
Issue Date: | 2020 |
Publisher: | ACM |
Citation: | Sfikas, K., & Liapis, A. (2020, September). Collaborative agent gameplay in the Pandemic board game. International Conference on the Foundations of Digital Games |
Abstract: | While artificial intelligence has been applied to control players’ decisions in board games for over half a century, little attention is given to games with no player competition. Pandemic is an exemplar collaborative board game where all players coordinate to overcome challenges posed by events occurring during the game’s progression. This paper proposes an artificial agent which controls all players’ actions and balances chances of winning versus risk of losing in this highly stochastic environment. The agent applies a Rolling Horizon Evolutionary Algorithm on an abstraction of the game-state that lowers the branching factor and simulates the game’s stochasticity. Results show that the proposed algorithm can find winning strategies more consistently in different games of varying difficulty. The impact of a number of state evaluation metrics is explored, balancing between optimistic strategies that favor winning and pessimistic strategies that guard against losing. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/80775 |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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3402942.3402943.pdf | 1.57 MB | Adobe PDF | View/Open |
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