44 citations · 71 across the 11 of their papers we have counts for
3 papers · 1 filter
Transfer RL via the Undo Maps Formalism
Abhi Gupta, Ted Moskovitz, David Alvarez-Melis +1
Transferring knowledge across domains is one of the most fundamental problems in machine learning, but doing so effectively in the context of reinforcement learning remains largely…
A Unified Theory of Dual-Process Control
Ted Moskovitz, Kevin Miller, Maneesh Sahani +1
Dual-process theories play a central role in both psychology and neuroscience, figuring prominently in fields ranging from executive control to reward-based learning to judgment an…
Minimum Description Length Control
Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani +1
We propose a novel framework for multitask reinforcement learning based on the minimum description length (MDL) principle. In this approach, which we term MDL-control (MDL-C), the…