This thesis investigates coordinating units through simultaneous coalition structuregeneration and task assignment in a complex Euclidean environment. The environmentused is StarCraft II, and the problem modeled and solved in the game is the distribution ofcombat units over the game’s map. The map was split into regions, and every region wasmodeled as a task to which the combat units were assigned.In a number of experiments, we compare the performance of our approach with thegame’s built-in bots. Against most of the non cheating options, our agent wins 20% of thegames played on a large map, against the Hard built-in bot. On a smaller and simpler mapit wins 22% of games played against the hardest non-cheating difficulty.One of the main limitations of the method used to solve the assignment was the utility function. Which should describe the quality of a coalition and the task assignment.However, as the utility function described the state’s utility better, the win rate increased.Therefore the result indicates that the simultaneous coalition structure generation and taskassignment work for unit distribution in a complex environment like StarCraft II if a sufficient utility function is provided.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-189432 |
Date | January 2022 |
Creators | Bergström, Edvin |
Publisher | Linköpings universitet, Institutionen för datavetenskap |
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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