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Paper · arXiv 2312.17653

LARP: Language-Agent Role Play for Open-World Games

Ming Yan, Ruihao Li, Hao Zhang, Hao Wang, Zhilan Yang, Ji Yan

34 upvotesDecember 24, 2023arXiv 预印本
AI 摘要

LARP is a language agent framework for open-world games, incorporating memory and decision-making capabilities to enhance interaction and coherence in a diverse range of applications.

cognitive architecturememory processingdecision-making assistantenvironment interaction modulelearnable action spacepostprocessing methodlanguage models

Abstract

Language agents have shown impressive problem-solving skills within defined settings and brief timelines. Yet, with the ever-evolving complexities of open-world simulations, there's a pressing need for agents that can flexibly adapt to complex environments and consistently maintain a long-term memory to ensure coherent actions. To bridge the gap between language agents and open-world games, we introduce Language Agent for Role-Playing (LARP), which includes a cognitive architecture that encompasses memory processing and a decision-making assistant, an environment interaction module with a feedback-driven learnable action space, and a postprocessing method that promotes the alignment of various personalities. The LARP framework refines interactions between users and agents, predefined with unique backgrounds and personalities, ultimately enhancing the gaming experience in open-world contexts. Furthermore, it highlights the diverse uses of language models in a range of areas such as entertainment, education, and various simulation scenarios. The project page is released at https://miao-ai-lab.github.io/LARP/.

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