activity
20172023
most citedLearning to Play No-Press Diplomacy with Best Response Policy Iteration

18 citations · 59 across the 12 of their papers we have counts for

collaborators

15 papers

cs.MA2023★ 1 cited

Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas

Udari Madhushani, Kevin R. McKee, John P. Agapiou +6

In social psychology, Social Value Orientation (SVO) describes an individual's propensity to allocate resources between themself and others. In reinforcement learning, SVO has been…

cs.MA2022

Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments

Ian Gemp, Thomas Anthony, Yoram Bachrach +24

The Game Theory & Multi-Agent team at DeepMind studies several aspects of multi-agent learning ranging from computing approximations to fundamental concepts in game theory to simul…

stat.ML2022

Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering

Elise van der Pol, Ian Gemp, Yoram Bachrach +1

Large graphs commonly appear in social networks, knowledge graphs, recommender systems, life sciences, and decision making problems. Summarizing large graphs by their high level pr…

cs.LG2022★ 2 cited

Learning Robust Real-Time Cultural Transmission without Human Data

Cultural General Intelligence Team, Avishkar Bhoopchand, Bethanie Brownfield +16

Cultural transmission is the domain-general social skill that allows agents to acquire and use information from each other in real-time with high fidelity and recall. In humans, it…

cs.AI2022★ 1 cited

Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria

Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas +7

A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate. This is particular…

cs.LG2021★ 3 cited

Collaborating with Humans without Human Data

DJ Strouse, Kevin R. McKee, Matt Botvinick +2

Collaborating with humans requires rapidly adapting to their individual strengths, weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement learning tech…