93 citations · 487 across the 42 of their papers we have counts for
5 papers · 1 filter
Mastering Atari 2600 Games with Discovered Options
Erik M. Lintunen, Marlos C. Machado
Temporal abstractions, often instantiated as options, have long been regarded as a mechanism for accelerating credit assignment, facilitating exploration, and enabling generalisati…
Learning Multiple Timescales for Goal-Conditioned Reinforcement Learning
Pedro Robles Dutenhefner, Dikshant Shehmar, Wagner Meira +1
Existing approaches to offline goal-conditioned reinforcement learning (GCRL) struggle with long-horizon tasks. Discounting shrinks value differences between distant states until t…
Accelerating Q-learning through Efficient Value-Sharing across Actions
Prabhat Nagarajan, Brett Daley, Martha White +1
Action values are foundational to many control algorithms such as Q-learning. Therefore, efficient action-value learning is central to reinforcement learning (RL). However, learnin…
Laplacian Representations for Decision-Time Planning
Dikshant Shehmar, Matthew Schlegel, Matthew E. Taylor +1
Planning with a learned model remains a key challenge in model-based reinforcement learning (RL). In decision-time planning, state representations are critical as they must support…
DROGO: Default Representation Objective via Graph Optimization in Reinforcement Learning
Hon Tik Tse, Marlos C. Machado
In computational reinforcement learning, the default representation (DR) and its principal eigenvector have been shown to be effective for a wide variety of applications, including…