15 citations · 16 across the 6 of their papers we have counts for
6 papers
Evaluating Collective Behaviour of Hundreds of LLM Agents
Richard Willis, Jianing Zhao, Yali Du +1
LLM-powered AI assistants acting on behalf of users can produce poor collective outcomes at scale. We introduce a framework for evaluating their emergent behaviour in social dilemm…
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…
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…
A Review of Cooperation in Multi-agent Learning
Yali Du, Joel Z. Leibo, Usman Islam +2
Cooperation in multi-agent learning (MAL) is a topic at the intersection of numerous disciplines, including game theory, economics, social sciences, and evolutionary biology. Resea…
Resolving social dilemmas with minimal reward transfer
Richard Willis, Yali Du, Joel Z Leibo +1
Social dilemmas present a significant challenge in multi-agent cooperation because individuals are incentivised to behave in ways that undermine socially optimal outcomes. Conseque…