【Proposal】Pokémon Battle Agent based on LLMs

Zihan Lv, Cen Qihang

Keywords: LLMs, SFT, Knowledge-Augmented Generation, Self-Consistency

TL;DR: We plan to develop a Pokémon battle agent based on LLMs.

Abstract: The rapid development of LLMs has led to widespread applications in interactive environments, particularly in gaming, where LLM agents demonstrate impressive decision-making and strategy execution capabilities. This paper focuses on developing a Pokémon battle agent based on LLMs. We combine techniques such as supervised fine-tuning, KAG and Self-Consistency to improve agent's contextual understanding and generate effective battle commands. Through experiments on Pokémon Showdown with robots and human, we will evaluate the model's win rates and strategic performance, aiming to contribute to the development of LLM agents capable of dynamic and complex environments.

Submission Number: 20