12 citations · 21 across the 5 of their papers we have counts for
3 papers · 1 filter
EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning
Siddharth Aravindan, Dixant Mittal, Wee Sun Lee
Posterior Sampling for Reinforcement Learning (PSRL) is a well-known algorithm that augments model-based reinforcement learning (MBRL) algorithms with Thompson sampling. PSRL maint…
State-Aware Variational Thompson Sampling for Deep Q-Networks
Siddharth Aravindan, Wee Sun Lee
Thompson sampling is a well-known approach for balancing exploration and exploitation in reinforcement learning. It requires the posterior distribution of value-action functions to…
An Analysis of Frame-skipping in Reinforcement Learning
Shivaram Kalyanakrishnan, Siddharth Aravindan, Vishwajeet Bagdawat +5
In the practice of sequential decision making, agents are often designed to sense state at regular intervals of time steps, , ignoring state information in between sensi…