7 citations · 16 across the 7 of their papers we have counts for
4 papers · 1 filter
Wasserstein Policy Optimization
David Pfau, Ian Davies, Diana Borsa +3
We introduce Wasserstein Policy Optimization (WPO), an actor-critic algorithm for reinforcement learning in continuous action spaces. WPO can be derived as an approximation to Wass…
One Step at a Time: Pros and Cons of Multi-Step Meta-Gradient Reinforcement Learning
Clément Bonnet, Paul Caron, Thomas Barrett +2
Self-tuning algorithms that adapt the learning process online encourage more effective and robust learning. Among all the methods available, meta-gradients have emerged as a promis…
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…
Learning to Model Opponent Learning
Ian Davies, Zheng Tian, Jun Wang
Multi-Agent Reinforcement Learning (MARL) considers settings in which a set of coexisting agents interact with one another and their environment. The adaptation and learning of oth…