General Modular Harness for LLM Agents in Multi-Turn Gaming Environments
Zhang, Yuxuan, Yu, Haoyang, Hu, Lanxiang, Jin, Haojian, Zhang, Hao
–arXiv.org Artificial Intelligence
We introduce a modular harness design for LLM agents that composes of perception, memory, and reasoning components, enabling a single LLM or VLM backbone to tackle a wide spectrum of multi turn gaming environments without domain-specific engineering. Using classic and modern game suites as low-barrier, high-diversity testbeds, our framework provides a unified workflow for analyzing how each module affects performance across dynamic interactive settings. Extensive experiments demonstrate that the harness lifts gameplay performance consistently over un-harnessed baselines and reveals distinct contribution patterns, for example, memory dominates in long-horizon puzzles while perception is critical in vision noisy arcades. These findings highlight the effectiveness of our modular harness design in advancing general-purpose agent, given the familiarity and ubiquity of games in everyday human experience.
arXiv.org Artificial Intelligence
Jul-17-2025
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- Research Report > New Finding (0.46)
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- Leisure & Entertainment > Games > Computer Games (1.00)
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