93 citations · 487 across the 42 of their papers we have counts for
3 papers · 1 filter
Generalization and Regularization in DQN
Jesse Farebrother, Marlos C. Machado, Michael Bowling
Deep reinforcement learning algorithms have shown an impressive ability to learn complex control policies in high-dimensional tasks. However, despite the ever-increasing performanc…
Count-Based Exploration with the Successor Representation
Marlos C. Machado, Marc G. Bellemare, Michael Bowling
In this paper we introduce a simple approach for exploration in reinforcement learning (RL) that allows us to develop theoretically justified algorithms in the tabular case but tha…
Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation
Craig Sherstan, Marlos C. Machado, Patrick M. Pilarski
Here we propose using the successor representation (SR) to accelerate learning in a constructive knowledge system based on general value functions (GVFs). In real-world settings li…