693 citations · 3.6k across the 81 of their papers we have counts for
14 papers · 1 filter
Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Chandler Smith, Marwa Abdulhai, Manfred Diaz +83
Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…
A Pragmatic View of AI Personhood
Joel Z. Leibo, Alexander Sasha Vezhnevets, William A. Cunningham +1
The emergence of agentic Artificial Intelligence (AI) is set to trigger a "Cambrian explosion" of new kinds of personhood. This paper proposes a pragmatic framework for navigating…
Beyond the high score: Prosocial ability profiles of multi-agent populations
Marko Tesic, Yue Zhao, Joel Z. Leibo +2
The development and evaluation of social capabilities in AI agents require complex environments where competitive and cooperative behaviours naturally emerge. While game-theoretic…
Virtual Agent Economies
Nenad Tomasev, Matija Franklin, Joel Z. Leibo +4
The rapid adoption of autonomous AI agents is giving rise to a new economic layer where agents transact and coordinate at scales and speeds beyond direct human oversight. We propos…
Multi-Actor Generative Artificial Intelligence as a Game Engine
Alexander Sasha Vezhnevets, Jayd Matyas, Logan Cross +6
Generative AI can be used in multi-actor environments with purposes ranging from social science modeling to interactive narrative and AI evaluation. Supporting this diversity of us…
Modeling human reputation-seeking behavior in a spatio-temporally complex public good provision game
Edward Hughes, Tina O. Zhu, Martin J. Chadwick +6
Multi-agent reinforcement learning algorithms are useful for simulating social behavior in settings that are too complex for other theoretical approaches like game theory. However,…
Using Large Language Models to Simulate Human Behavioural Experiments: Port of Mars
Oliver Slumbers, Joel Z. Leibo, Marco A. Janssen
Collective risk social dilemmas (CRSD) highlight a trade-off between individual preferences and the need for all to contribute toward achieving a group objective. Problems such as…
Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt
Joel Z. Leibo, Alexander Sasha Vezhnevets, William A. Cunningham +3
Artificial Intelligence (AI) systems are increasingly placed in positions where their decisions have real consequences, e.g., moderating online spaces, conducting research, and adv…
Meaning Is Not A Metric: Using LLMs to make cultural context legible at scale
Cody Kommers, Drew Hemment, Maria Antoniak +4
This position paper argues that large language models (LLMs) can make cultural context, and therefore human meaning, legible at an unprecedented scale in AI-based sociotechnical sy…
SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas
Zihao Guo, Shuqing Shi, Richard Willis +3
Sequential social dilemmas pose a significant challenge in the field of multi-agent reinforcement learning (MARL), requiring environments that accurately reflect the tension betwee…
Multi-Agent Risks from Advanced AI
Lewis Hammond, Alan Chan, Jesse Clifton +41
The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These s…
Simulation Streams: A Programming Paradigm for Controlling Large Language Models and Building Complex Systems with Generative AI
Peter Sunehag, Joel Z. Leibo
We introduce Simulation Streams, a programming paradigm designed to efficiently control and leverage Large Language Models (LLMs) for complex, dynamic simulations and agentic workf…
Will Systems of LLM Agents Cooperate: An Investigation into a Social Dilemma
Richard Willis, Yali Du, Joel Z Leibo +1
As autonomous agents become more prevalent, understanding their collective behaviour in strategic interactions is crucial. This study investigates the emergent cooperative tendenci…
Quantifying the Self-Interest Level of Markov Social Dilemmas
Richard Willis, Yali Du, Joel Z Leibo +1
This paper introduces a novel method for estimating the self-interest level of Markov social dilemmas. We extend the concept of self-interest level from normal-form games to Markov…