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Found 5 papers, 3 papers with code
Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents
In contrast, agents tested in dynamic robot environments face limitations due to simplistic environments with only a few objects and interactions.
PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games
To bridge this gap, we introduce PyTAG, a Python API for interacting with the Tabletop Games framework (TAG).
Portfolio Search and Optimization for General Strategy Game-Playing
Portfolio methods represent a simple but efficient type of action abstraction which has shown to improve the performance of search-based agents in a range of strategy games.
Generating Diverse and Competitive Play-Styles for Strategy Games
Designing agents that are able to achieve different play-styles while maintaining a competitive level of play is a difficult task, especially for games for which the research community has not found super-human performance yet, like strategy games.
The Design Of "Stratega": A General Strategy Games Framework
Stratega, a general strategy games framework, has been designed to foster research on computational intelligence for strategy games.
