76 citations · 77 across the 12 of their papers we have counts for
14 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…
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…
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…
Differentiable Information Enhanced Model-Based Reinforcement Learning
Xiaoyuan Zhang, Xinyan Cai, Bo Liu +4
Differentiable environments have heralded new possibilities for learning control policies by offering rich differentiable information that facilitates gradient-based methods. In co…
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…
On the Emergence of Symmetrical Reality
Zhenliang Zhang, Zeyu Zhang, Ziyuan Jiao +4
Artificial intelligence (AI) has revolutionized human cognitive abilities and facilitated the development of new AI entities capable of interacting with humans in both physical and…
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…
AI Alignment: A Comprehensive Survey
Jiaming Ji, Tianyi Qiu, Boyuan Chen +23
AI alignment aims to make AI systems behave in line with human intentions and values. As AI systems grow more capable, so do risks from misalignment. To provide a comprehensive and…