11 papers
Modeling Decision-Making with Will for Cooperation in Social Dilemmas
Yizhe Huang, Bin Ling, Song-Chun Zhu +1
Standard rational actor models often attribute cooperation failures in social dilemmas to insufficient incentives, overlooking the destabilizing effects of continuous utility maxim…
Learning to cooperate with emergent reputation via multi-agent reinforcement learning
Xinwei Song, Yizhe Huang, Dengji Zhao +1
Reputation, the aggregation of peer assessments diffused through social networks, is a pivotal mechanism for promoting cooperation in social dilemmas ubiquitous to distributed mult…
ECom-Bench: Can LLM Agent Resolve Real-World E-commerce Customer Support Issues?
Haoxin Wang, Xianhan Peng, Xucheng Huang +5
In this paper, we introduce ECom-Bench, the first benchmark framework for evaluating LLM agent with multimodal capabilities in the e-commerce customer support domain. ECom-Bench fe…
World Models Should Prioritize the Unification of Physical and Social Dynamics
Xiaoyuan Zhang, Chengdong Ma, Yizhe Huang +5
World models, which explicitly learn environmental dynamics to lay the foundation for planning, reasoning, and decision-making, are rapidly advancing in predicting both physical dy…
Social World Model-Augmented Mechanism Design Policy Learning
Xiaoyuan Zhang, Yizhe Huang, Chengdong Ma +6
Designing adaptive mechanisms to align individual and collective interests remains a central challenge in artificial social intelligence. Existing methods often struggle with model…
ToMPO: Training LLM Strategic Decision Making from a Multi-Agent Perspective
Yiwen Zhang, Ziang Chen, Fanqi Kong +2
Large Language Models (LLMs) have been used to make decisions in complex scenarios, where they need models to think deeply, reason logically, and decide wisely. Many existing studi…