4 papers
Convergent Reinforcement Learning Algorithms for Stochastic Shortest Path Problem
Soumyajit Guin, Shalabh Bhatnagar
In this paper we propose two algorithms in the tabular setting and an algorithm for the function approximation setting for the Stochastic Shortest Path (SSP) problem. SSP problems…
An Actor-Critic Algorithm with Function Approximation for Risk Sensitive Cost Markov Decision Processes
Soumyajit Guin, Vivek S. Borkar, Shalabh Bhatnagar
In this paper, we consider the risk-sensitive cost criterion with exponentiated costs for Markov decision processes and develop a model-free policy gradient algorithm in this setti…
A policy gradient approach for Finite Horizon Constrained Markov Decision Processes
Soumyajit Guin, Shalabh Bhatnagar
The infinite horizon setting is widely adopted for problems of reinforcement learning (RL). These invariably result in stationary policies that are optimal. In many situations, fin…
Actor-Critic or Critic-Actor? A Tale of Two Time Scales
Shalabh Bhatnagar, Vivek S. Borkar, Soumyajit Guin
We revisit the standard formulation of tabular actor-critic algorithm as a two time-scale stochastic approximation with value function computed on a faster time-scale and policy co…