LARP: Language-Agent Role Play for Open-World Games
Authors: name: Ming Yan, name: Ruihao Li, name: Hao Zhang, name: Hao Wang, name: Zhilan Yang, name: Ji Yan

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/.