23 citations · 32 across the 16 of their papers we have counts for
3 papers · 1 filter
Multi-step Greedy Reinforcement Learning Algorithms
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
Multi-step greedy policies have been extensively used in model-based reinforcement learning (RL), both when a model of the environment is available (e.g.,~in the game of Go) and wh…
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
Manan Tomar, Akhil Sathuluri, Balaraman Ravindran
Shaping in humans and animals has been shown to be a powerful tool for learning complex tasks as compared to learning in a randomized fashion. This makes the problem less complex a…
Successor Options: An Option Discovery Framework for Reinforcement Learning
Rahul Ramesh, Manan Tomar, Balaraman Ravindran
The options framework in reinforcement learning models the notion of a skill or a temporally extended sequence of actions. The discovery of a reusable set of skills has typically e…