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20182026
most citedA Survey of Deep Reinforcement Learning in Video Games

149 citations · 219 across the 20 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.LG2025

Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games

Runyu Lu, Peng Zhang, Ruochuan Shi +5

Equilibrium learning in adversarial games is an important topic widely examined in the fields of game theory and reinforcement learning (RL). Pursuit-evasion game (PEG), as an impo…

cs.CL2025

CriticSearch: Fine-Grained Credit Assignment for Search Agents via a Retrospective Critic

Yaocheng Zhang, Haohuan Huang, Zijun Song +4

Tool-Integrated Reasoning (TIR) with search engines enables large language models to iteratively retrieve up-to-date external knowledge, enhancing adaptability and generalization i…

cs.LG2025

ARAC: Adaptive Regularized Multi-Agent Soft Actor-Critic in Graph-Structured Adversarial Games

Ruochuan Shi, Runyu Lu, Yuanheng Zhu +1

In graph-structured multi-agent reinforcement learning (MARL) adversarial tasks such as pursuit and confrontation, agents must coordinate under highly dynamic interactions, where s…

cs.LG2025

R2PS: Worst-Case Robust Real-Time Pursuit Strategies under Partial Observability

Runyu Lu, Ruochuan Shi, Yuanheng Zhu +1

Computing worst-case robust strategies in pursuit-evasion games (PEGs) is time-consuming, especially when real-world factors like partial observability are considered. While import…

cs.RO2025

Empowering Multi-Robot Cooperation via Sequential World Models

Zijie Zhao, Honglei Guo, Shengqian Chen +4

Model-based reinforcement learning (MBRL) has achieved remarkable success in robotics due to its high sample efficiency and planning capability. However, extending MBRL to physical…

cs.CL2025

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning

Yuqian Fu, Tinghong Chen, Jiajun Chai +7

Large language models (LLMs) have achieved remarkable progress in reasoning tasks, yet the optimal integration of Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) remai…

cs.AI2025

DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy

Kaixuan Xu, Jiajun Chai, Sicheng Li +3

Diplomacy is a complex multiplayer game that requires both cooperation and competition, posing significant challenges for AI systems. Traditional methods rely on equilibrium search…

cs.LG2025

RLAE: Reinforcement Learning-Assisted Ensemble for LLMs

Yuqian Fu, Yuanheng Zhu, Jiajun Chai +4

Ensembling large language models (LLMs) can effectively combine diverse strengths of different models, offering a promising approach to enhance performance across various tasks. Ho…