192 citations · 223 across the 3 of their papers we have counts for
3 papers
Fully Distributed Actor-Critic Architecture for Multitask Deep Reinforcement Learning
Sergio Valcarcel Macua, Ian Davies, Aleksi Tukiainen +1
We propose a fully distributed actor-critic architecture, named Diff-DAC, with application to multitask reinforcement learning (MRL). During the learning process, agents communicat…
A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity
Pablo Hernandez-Leal, Michael Kaisers, Tim Baarslag +1
The key challenge in multiagent learning is learning a best response to the behaviour of other agents, which may be non-stationary: if the other agents adapt their strategy as well…
A Polynomial-time Nash Equilibrium Algorithm for Repeated Stochastic Games
Enrique Munoz de Cote, Michael L. Littman
We present a polynomial-time algorithm that always finds an (approximate) Nash equilibrium for repeated two-player stochastic games. The algorithm exploits the folk theorem to deri…