29 citations · 46 across the 3 of their papers we have counts for
3 papers · 1 filter
Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning
Sahil Sharma, Aravind Suresh, Rahul Ramesh +1
Deep Reinforcement Learning (DRL) methods have performed well in an increasing numbering of high-dimensional visual decision making domains. Among all such visual decision making p…
Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning
Sahil Sharma, Girish Raguvir J, Srivatsan Ramesh +1
Reinforcement Learning (RL) can model complex behavior policies for goal-directed sequential decision making tasks. A hallmark of RL algorithms is Temporal Difference (TD) learning…
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning
Sahil Sharma, Aravind Srinivas, Balaraman Ravindran
Reinforcement Learning algorithms can learn complex behavioral patterns for sequential decision making tasks wherein an agent interacts with an environment and acquires feedback in…