693 citations · 3.6k across the 81 of their papers we have counts for
6 papers · 1 filter
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017
M. Botvinick, D. G. T. Barrett, P. Battaglia +16
We agree with Lake and colleagues on their list of key ingredients for building humanlike intelligence, including the idea that model-based reasoning is essential. However, we favo…
Symmetric Decomposition of Asymmetric Games
Karl Tuyls, Julien Perolat, Marc Lanctot +6
We introduce new theoretical insights into two-population asymmetric games allowing for an elegant symmetric decomposition into two single population symmetric games. Specifically,…
A multi-agent reinforcement learning model of common-pool resource appropriation
Julien Perolat, Joel Z. Leibo, Vinicius Zambaldi +3
Humanity faces numerous problems of common-pool resource appropriation. This class of multi-agent social dilemma includes the problems of ensuring sustainable use of fresh water, c…
Value-Decomposition Networks For Cooperative Multi-Agent Learning
Peter Sunehag, Guy Lever, Audrunas Gruslys +8
We study the problem of cooperative multi-agent reinforcement learning with a single joint reward signal. This class of learning problems is difficult because of the often large co…
Deep Q-learning from Demonstrations
Todd Hester, Matej Vecerik, Olivier Pietquin +11
Deep reinforcement learning (RL) has achieved several high profile successes in difficult decision-making problems. However, these algorithms typically require a huge amount of dat…
Multi-agent Reinforcement Learning in Sequential Social Dilemmas
Joel Z. Leibo, Vinicius Zambaldi, Marc Lanctot +2
Matrix games like Prisoner's Dilemma have guided research on social dilemmas for decades. However, they necessarily treat the choice to cooperate or defect as an atomic action. In…