A Survey on the Application of Agentic AI in Gaming

Since the release of Practices for Governing Agentic AI Systems by OpenAI in 2023, the emerging paradigm of Agentic AI (Artificial Intelligence) has gradually attracted academic attention. Unlike traditional AI systems that rely on structured presets and extensive human intervention, Agentic AI refers to intelligent systems capable of understanding task objectives, adapting to complex environments, and autonomously completing tasks with minimal human oversight. Its advantages in adaptability, decision-making, and self-management make it particularly suited to dynamic and rapidly changing real-world scenarios. This paper first outlines the definition, core characteristics, and primary enabling technologies of Agentic AI, emphasizing that, to date, no deployed system in the gaming domain fully embodies all of its defining features. To explore potential pathways toward practical implementation, the paper analyzes several recent large-model-based agentssuch as SIMA, and ChatRPG v2, that, while falling short of the full Agentic AI standard, exhibit partial alignment through capabilities such as autonomous instruction comprehension, long-term task execution, multi-environment adaptation, and low-intervention deployment. These systems can therefore be regarded as generative agents with Agentic characteristics, offering valuable insights for future research directions and technical architectures. Finally, the paper proposes using gaming environments as low-cost, low-risk, and highly controllable testbeds for validating key capabilities, accumulating deployment experience, and accelerating the transition of Agentic AI into real-world applications, thereby advancing game AI from scripted logic toward higher levels of autonomous intelligence.

Authors

Institutions

Publication Details

Journal
Applied and Computational Engineering
Published
2025-10-14
DOI
https://doi.org/10.54254/2755-2721/2025.ld27634
Primary Topic
Diverse Topics in Contemporary Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Survey on the Application of Agentic AI in Gaming

Ling Xu
Applied and Computational Engineering
Diverse Topics in Contemporary Research
article

A Survey on the Application of Agentic AI in Gaming

Ling Xu
article en

Abstract

Since the release of Practices for Governing Agentic AI Systems by OpenAI in 2023, the emerging paradigm of Agentic AI (Artificial Intelligence) has gradually attracted academic attention. Unlike traditional AI systems that rely on structured presets and extensive human intervention, Agentic AI refers to intelligent systems capable of understanding task objectives, adapting to complex environments, and autonomously completing tasks with minimal human oversight. Its advantages in adaptability, decision-making, and self-management make it particularly suited to dynamic and rapidly changing real-world scenarios. This paper first outlines the definition, core characteristics, and primary enabling technologies of Agentic AI, emphasizing that, to date, no deployed system in the gaming domain fully embodies all of its defining features. To explore potential pathways toward practical implementation, the paper analyzes several recent large-model-based agentssuch as SIMA, and ChatRPG v2, that, while falling short of the full Agentic AI standard, exhibit partial alignment through capabilities such as autonomous instruction comprehension, long-term task execution, multi-environment adaptation, and low-intervention deployment. These systems can therefore be regarded as generative agents with Agentic characteristics, offering valuable insights for future research directions and technical architectures. Finally, the paper proposes using gaming environments as low-cost, low-risk, and highly controllable testbeds for validating key capabilities, accumulating deployment experience, and accelerating the transition of Agentic AI into real-world applications, thereby advancing game AI from scripted logic toward higher levels of autonomous intelligence.

Applied and Computational EngineeringVol. 191(1)
Truman State University (US)
Openalex Percentile: Top 66%
Diverse Topics in Contemporary Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Survey on the Application of Agentic AI in Gaming — Ling Xu · Applied and Computational Engineering (2025) | TGRS Research Map | TGRS