1 citations · 1 across the 6 of their papers we have counts for
8 papers
Adaptive Punishment for Cooperation in Mixed-Motive Games
Min Tang, Fanqi Kong, Linyuan Lü +1
Mixed-motive scenarios are ubiquitous in real-world multi-agent interactions, where self-interested agents often defect for immediate rewards, overlooking the potential of altruist…
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…
Enhancing LLM-Based Social Bot via an Adversarial Learning Framework
Fanqi Kong, Xiaoyuan Zhang, Xinyu Chen +3
Developing Large Language Model (LLM) agents that exhibit human-like behavior, encompassing not only individual heterogeneity rooted in unique user profiles but also adaptive respo…
Aegis: Automated Error Generation and Attribution for Multi-Agent Systems
Fanqi Kong, Ruijie Zhang, Huaxiao Yin +7
Large language model based multi-agent systems (MAS) have unlocked significant advancements in tackling complex problems, but their increasing capability introduces a structural fr…
SIV-Bench: A Video Benchmark for Social Interaction Understanding and Reasoning
Fanqi Kong, Weiqin Zu, Xinyu Chen +3
Understanding social interaction, which encompasses perceiving numerous and subtle multimodal cues, inferring unobservable mental states and relations, and dynamically predicting o…
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…
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…