1 citations · 1 across the 11 of their papers we have counts for
12 papers
Grounded Normative Rule Generation with Structured Search
Fanqi Kong, Huaxiao Yin, Ruijie Zhang +5
Normative rules like institutional charters and workplace policies must be both human-readable and operationally verifiable against actual environment records. However, current lan…
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…
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…
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…
MemOrb: A Plug-and-Play Verbal-Reinforcement Memory Layer for E-Commerce Customer Service
Yizhe Huang, Yang Liu, Ruiyu Zhao +3
Large Language Model-based agents(LLM-based agents) are increasingly deployed in customer service, yet they often forget across sessions, repeat errors, and lack mechanisms for con…
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…
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
Yizhe Huang, Xingbo Wang, Hao Liu +7
Traditional interactive environments limit agents' intelligence growth with fixed tasks. Recently, single-agent environments address this by generating new tasks based on agent act…
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games
Fanqi Kong, Yizhe Huang, Song-Chun Zhu +2
Real-world multi-agent scenarios often involve mixed motives, demanding altruistic agents capable of self-protection against potential exploitation. However, existing approaches of…
Data-driven Multistage Distributionally Robust Linear Optimization with Nested Distance
Rui Gao, Rohit Arora, Yizhe Huang
We study multistage distributionally robust linear optimization, where the uncertainty set is defined as a ball of distribution centered at a scenario tree using the nested distanc…
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
Yizhe Huang, Anji Liu, Fanqi Kong +3
Despite the recent successes of multi-agent reinforcement learning (MARL) algorithms, efficiently adapting to co-players in mixed-motive environments remains a significant challeng…