1 citations · 1 across the 6 of their papers we have counts for
6 papers
SAGA: Scene-Aware, Goal-Evolving Agents for Long-Horizon Strategy Game Planning
Tianyu Jin, Shuo Chen, Yida Wang +5
Grand-strategy games such as Civilization pose a distinctive long-horizon planning problem: an agent must divide one shared resource pool among six competing domains -- technology,…
Hierarchical Multiagent Reinforcement Learning for Multi-Group Tax Game
Honglei Guo, Yuhan Zhao, Yexin Li +1
Taxation is a fundamental instrument of economic policy and has long been studied through economic models. However, most existing taxation models focus on interactions within a sin…
CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning
Yexin Li
Exploration remains a fundamental challenge in reinforcement learning, as many existing methods either lack theoretical guarantees or fall short in practical effectiveness. In this…
Are the Values of LLMs Structurally Aligned with Humans? A Causal Perspective
Yipeng Kang, Junqi Wang, Yexin Li +8
As large language models (LLMs) become increasingly integrated into critical applications, aligning their behavior with human values presents significant challenges. Current method…
A Contextual Combinatorial Bandit Approach to Negotiation
Yexin Li, Zhancun Mu, Siyuan Qi
Learning effective negotiation strategies poses two key challenges: the exploration-exploitation dilemma and dealing with large action spaces. However, there is an absence of learn…
CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents
Siyuan Qi, Shuo Chen, Yexin Li +11
The generalization of decision-making agents encompasses two fundamental elements: learning from past experiences and reasoning in novel contexts. However, the predominant emphasis…