The development of game agents holds a critical role in advancing towards
Artificial General Intelligence (AGI). The progress of LLMs and their
multimodal counterparts (MLLMs) offers an unprecedented opportunity to evolve
and empower game agents with human-like decision-making capabilities in complex
computer game environments. This paper provides a comprehensive overview of
LLM-based game agents from a holistic viewpoint. First, we introduce the
conceptual architecture of LLM-based game agents, centered around six essential
functional components: perception, memory, thinking, role-playing, action, and
learning. Second, we survey existing representative LLM-based game agents
documented in the literature with respect to methodologies and adaptation
agility across six genres of games, including adventure, communication,
competition, cooperation, simulation, and crafting & exploration games.
Finally, we present an outlook of future research and development directions in
this burgeoning field. A curated list of relevant papers is maintained and made
accessible at: this https URL

利用 LLMs 在复杂的电脑游戏环境中赋予游戏智能体人类般的决策能力，以推进人工智能 (AGI) 的发展，并提供了 LLM 基础的游戏智能体的综述，包括感知、记忆、思考、角色扮演、行动和学习的六个关键组成部分，调研了六种游戏类型的现有代表性 LLM 基础游戏智能体，并展望了未来的研究和发展方向。

基于大型语言模型的游戏智能代理调查

A Survey on Large Language Model-Based Game Agents

Game agents such as opponents, non-player characters, and teammates are
central to player experiences in many modern games. As the landscape of AI
techniques used in the games industry evolves to adopt machine learning (ML)
more widely, it is vital that the research community learn from the best
practices cultivated within the industry over decades creating agents. However,
although commercial game agent creation pipelines are more mature than those
based on ML, opportunities for improvement still abound. As a foundation for
shared progress identifying research opportunities between researchers and
practitioners, we interviewed seventeen game agent creators from AAA studios,
indie studios, and industrial research labs about the challenges they
experienced with their professional workflows. Our study revealed several open
challenges ranging from design to implementation and evaluation. We compare
with literature from the research community that address the challenges
identified and conclude by highlighting promising directions for future
research supporting agent creation in the games industry.

该研究通过对 AAA 工作室、独立工作室和工业研究实验室的 17 位游戏代理创作者的访谈，揭示了游戏代理制作面临的设计、实现和评估等几个方面的挑战。并与学术研究相比较，指出未来研究中支持游戏产业代理创作的方向。