Tabletop games have within recent years evolvedto become more and more complex, such as through the useof dynamic rules, permanently changing how the game worksafter a playthrough, and players playing different roles in thegame. This leads to unique challenges for Artificial Intelligence.A Tabletop Games Framework (TAG) is a framework intended topromote research within general AI for modern tabletop games.Rolling Horizon Evolutionary Algorithms (RHEA) are a typeof algorithms that have been applied to games with successin the past. By implementing a RHEA agent we can studyhow it compares to other types of agents such as Monte CarloTree Search and Random Mutation Hill Climbing agents. Ofparticular interest is the game Pandemic (2008), as the existingagents are unable to win at it.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-52865 |
Date | January 2022 |
Creators | Smedman, Mattias |
Publisher | Malmö universitet, Fakulteten för teknik och samhälle (TS) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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