360 citations · 2.7k across the 150 of their papers we have counts for
4 papers · 2 filters
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction
Vishal Jain, William Fedus, Hugo Larochelle +2
Text-based games are a natural challenge domain for deep reinforcement learning algorithms. Their state and action spaces are combinatorially large, their reward function is sparse…
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning
Tianyu Li, Bogdan Mazoure, Doina Precup +1
Learning and planning in partially-observable domains is one of the most difficult problems in reinforcement learning. Traditional methods consider these two problems as independen…
Option-Critic in Cooperative Multi-agent Systems
Jhelum Chakravorty, Nadeem Ward, Julien Roy +4
In this paper, we investigate learning temporal abstractions in cooperative multi-agent systems, using the options framework (Sutton et al, 1999). First, we address the planning pr…
The Termination Critic
Anna Harutyunyan, Will Dabney, Diana Borsa +3
In this work, we consider the problem of autonomously discovering behavioral abstractions, or options, for reinforcement learning agents. We propose an algorithm that focuses on th…