@article{LI2025100894,
title = {A concise review of intelligent game agent},
journal = {Entertainment Computing},
volume = {52},
pages = {100894},
year = {2025},
issn = {1875-9521},
doi = {https://doi.org/10.1016/j.entcom.2024.100894},
url = {https://www.sciencedirect.com/science/article/pii/S1875952124002623},
author = {Hui Li and Xinyi Pang and Bixia Sun and Kexin Liu},
keywords = {Intelligent agent, Artificial intelligence, Monte Carlo tree, Reinforcement learning, Large language models},
abstract = {Intelligent game agents are crafted using AI technologies to mimic player behavior and make decisions autonomously. Over the past decades, the scope of intelligent agents has broadened from chess to encompass content generation, player modeling, and result prediction, reflecting the field’s evolving and multifaceted nature. In this paper, we conduct a systematic review of recent literature on intelligent methods and applications of game agents, along with general game agent frameworks. Our findings suggest that creating general intelligent agents remains a significant challenge, yet it is worthwhile to explore methods that better integrate the strengths of different techniques to build more robust and adaptable intelligent game agents.}
}