3 citations · 5 across the 14 of their papers we have counts for
15 papers
PlanPO: Group Planning-Aware Policy Optimization for Multi-Turn Agentic LLMs
Dayang Liang, Liyuan He, Xuan Feng +3
Group-relative policy optimization has emerged as a key paradigm for training agentic large language models (LLMs) on multi-turn interactive tasks. However, most existing variants…
DEpiABS: Differentiable Epidemic Agent-Based Simulator
Zhijian Gao, Shuxin Li, Bo An
The COVID-19 pandemic highlighted the limitations of existing epidemic simulation tools. These tools provide information that guides non-pharmaceutical interventions (NPIs), yet ma…
Tree-Based Stochastic Optimization for Solving Large-Scale Urban Network Security Games
Shuxin Zhuang, Linjian Meng, Shuxin Li +2
Urban Network Security Games (UNSGs), which model the strategic allocation of limited security resources on city road networks, are critical for urban safety. However, finding a Na…
Nondeterministic Polynomial-time Problem Challenge: An Ever-Scaling Reasoning Benchmark for LLMs
Chang Yang, Ruiyu Wang, Junzhe Jiang +9
Reasoning is the fundamental capability of large language models (LLMs). Due to the rapid progress of LLMs, there are two main issues of current benchmarks: i) these benchmarks can…
GraphChase: A Platform and Benchmark for Urban Network Security Games
Shuxin Zhuang, Shuxin Li, Tianji Yang +4
After the achievement of solving two-player zero-sum games, more AI researchers focus on solving multiplayer games. Urban Network Security Games (\textbf{UNSGs}) represent a class…
In-Context Exploiter for Extensive-Form Games
Shuxin Li, Chang Yang, Youzhi Zhang +5
Nash equilibrium (NE) is a widely adopted solution concept in game theory due to its stability property. However, we observe that the NE strategy might not always yield the best re…
Configurable Mirror Descent: Towards a Unification of Decision Making
Pengdeng Li, Shuxin Li, Chang Yang +5
Decision-making problems, categorized as single-agent, e.g., Atari, cooperative multi-agent, e.g., Hanabi, competitive multi-agent, e.g., Hold'em poker, and mixed cooperative and c…
Reinforcement Nash Equilibrium Solver
Xinrun Wang, Chang Yang, Shuxin Li +4
Nash Equilibrium (NE) is the canonical solution concept of game theory, which provides an elegant tool to understand the rationalities. Though mixed strategy NE exists in any game…
Grasper: A Generalist Pursuer for Pursuit-Evasion Problems
Pengdeng Li, Shuxin Li, Xinrun Wang +5
Pursuit-evasion games (PEGs) model interactions between a team of pursuers and an evader in graph-based environments such as urban street networks. Recent advancements have demonst…
Self-adaptive PSRO: Towards an Automatic Population-based Game Solver
Pengdeng Li, Shuxin Li, Chang Yang +4
Policy-Space Response Oracles (PSRO) as a general algorithmic framework has achieved state-of-the-art performance in learning equilibrium policies of two-player zero-sum games. How…
Population-size-Aware Policy Optimization for Mean-Field Games
Pengdeng Li, Xinrun Wang, Shuxin Li +2
In this work, we attempt to bridge the two fields of finite-agent and infinite-agent games, by studying how the optimal policies of agents evolve with the number of agents (populat…
Offline Equilibrium Finding
Shuxin Li, Xinrun Wang, Youzhi Zhang +4
Offline reinforcement learning (offline RL) is an emerging field that has recently begun gaining attention across various application domains due to its ability to learn strategies…
A Unified Perspective on Deep Equilibrium Finding
Xinrun Wang, Jakub Cerny, Shuxin Li +4
Extensive-form games provide a versatile framework for modeling interactions of multiple agents subjected to imperfect observations and stochastic events. In recent years, two para…
Solving Large-Scale Extensive-Form Network Security Games via Neural Fictitious Self-Play
Wanqi Xue, Youzhi Zhang, Shuxin Li +3
Securing networked infrastructures is important in the real world. The problem of deploying security resources to protect against an attacker in networked domains can be modeled as…
CFR-MIX: Solving Imperfect Information Extensive-Form Games with Combinatorial Action Space
Shuxin Li, Youzhi Zhang, Xinrun Wang +2
In many real-world scenarios, a team of agents coordinate with each other to compete against an opponent. The challenge of solving this type of game is that the team's joint action…