34 citations · 111 across the 48 of their papers we have counts for
4 papers · 1 filter
Direct Behavior Specification via Constrained Reinforcement Learning
Julien Roy, Roger Girgis, Joshua Romoff +2
The standard formulation of Reinforcement Learning lacks a practical way of specifying what are admissible and forbidden behaviors. Most often, practitioners go about the task of b…
Neural Algorithmic Reasoners are Implicit Planners
Andreea Deac, Petar Veličković, Ognjen Milinković +3
Implicit planning has emerged as an elegant technique for combining learned models of the world with end-to-end model-free reinforcement learning. We study the class of implicit pl…
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
Evgenii Nikishin, Romina Abachi, Rishabh Agarwal +1
The shortcomings of maximum likelihood estimation in the context of model-based reinforcement learning have been highlighted by an increasing number of papers. When the model class…
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning
Dilip Arumugam, Peter Henderson, Pierre-Luc Bacon
How do we formalize the challenge of credit assignment in reinforcement learning? Common intuition would draw attention to reward sparsity as a key contributor to difficult credit…