2 citations · 2 across the 8 of their papers we have counts for
3 papers · 1 filter
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
Gandharv Patil, Prashanth L. A., Dheeraj Nagaraj +1
We study the finite-time behaviour of the popular temporal difference (TD) learning algorithm when combined with tail-averaging. We derive finite time bounds on the parameter error…
A Survey of Risk-Aware Multi-Armed Bandits
Vincent Y. F. Tan, Prashanth L. A., Krishna Jagannathan
In several applications such as clinical trials and financial portfolio optimization, the expected value (or the average reward) does not satisfactorily capture the merits of a dru…
A policy gradient approach for optimization of smooth risk measures
Nithia Vijayan, Prashanth L. A
We propose policy gradient algorithms for solving a risk-sensitive reinforcement learning (RL) problem in on-policy as well as off-policy settings. We consider episodic Markov deci…