3 citations · 6 across the 5 of their papers we have counts for
5 papers
Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement
Samuel Neumann, Sungsu Lim, Ajin Joseph +3
Many policy gradient methods are variants of Actor-Critic (AC), where a value function (critic) is learned to facilitate updating the parameterized policy (actor). The update to th…
An Online Prediction Algorithm for Reinforcement Learning with Linear Function Approximation using Cross Entropy Method
Ajin George Joseph, Shalabh Bhatnagar
In this paper, we provide two new stable online algorithms for the problem of prediction in reinforcement learning, \emph{i.e.}, estimating the value function of a model-free Marko…
A Cross Entropy based Optimization Algorithm with Global Convergence Guarantees
Ajin George Joseph, Shalabh Bhatnagar
The cross entropy (CE) method is a model based search method to solve optimization problems where the objective function has minimal structure. The Monte-Carlo version of the CE me…
An Incremental Off-policy Search in a Model-free Markov Decision Process Using a Single Sample Path
Ajin George Joseph, Shalabh Bhatnagar
In this paper, we consider a modified version of the control problem in a model free Markov decision process (MDP) setting with large state and action spaces. The control problem m…
A Cross Entropy based Stochastic Approximation Algorithm for Reinforcement Learning with Linear Function Approximation
Ajin George Joseph, Shalabh Bhatnagar
In this paper, we provide a new algorithm for the problem of prediction in Reinforcement Learning, \emph{i.e.}, estimating the Value Function of a Markov Reward Process (MRP) using…