125 citations · 130 across the 2 of their papers we have counts for
4 papers
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman +1
Sharing parameters in multi-agent deep reinforcement learning has played an essential role in allowing algorithms to scale to a large number of agents. Parameter sharing between ag…
Variational Autoencoders for Opponent Modeling in Multi-Agent Systems
Georgios Papoudakis, Stefano V. Albrecht
Multi-agent systems exhibit complex behaviors that emanate from the interactions of multiple agents in a shared environment. In this work, we are interested in controlling one agen…
Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
Georgios Papoudakis, Filippos Christianos, Arrasy Rahman +1
Recent developments in deep reinforcement learning are concerned with creating decision-making agents which can perform well in various complex domains. A particular approach which…
Deep Reinforcement Learning for Doom using Unsupervised Auxiliary Tasks
Georgios Papoudakis, Kyriakos C. Chatzidimitriou, Pericles A. Mitkas
Recent developments in deep reinforcement learning have enabled the creation of agents for solving a large variety of games given a visual input. These methods have been proven suc…