187 citations · 482 across the 18 of their papers we have counts for
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Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods
Peter Henderson, Joshua Romoff, Joelle Pineau
Recent analyses of certain gradient descent optimization methods have shown that performance can degrade in some settings - such as with stochasticity or implicit momentum. In deep…
TarMAC: Targeted Multi-Agent Communication
Abhishek Das, Théophile Gervet, Joshua Romoff +4
We propose a targeted communication architecture for multi-agent reinforcement learning, where agents learn both what messages to send and whom to address them to while performing…
Randomized Value Functions via Multiplicative Normalizing Flows
Ahmed Touati, Harsh Satija, Joshua Romoff +2
Randomized value functions offer a promising approach towards the challenge of efficient exploration in complex environments with high dimensional state and action spaces. Unlike t…
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
Joshua Romoff, Peter Henderson, Alexandre Piché +2
Reinforcement Learning (RL) agents require the specification of a reward signal for learning behaviours. However, introduction of corrupt or stochastic rewards can yield high varia…