Search Results for author:
Found 3 papers, 0 papers with code
An Online Prediction Algorithm for Reinforcement Learning with Linear Function Approximation using Cross Entropy Method
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 Markov reward process using the linear function approximation architecture and with memory and computation costs scaling quadratically in the size of the feature set.
A Cross Entropy based Optimization Algorithm with Global Convergence Guarantees
The cross entropy (CE) method is a model based search method to solve optimization problems where the objective function has minimal structure.
An Incremental Off-policy Search in a Model-free Markov Decision Process Using a Single Sample Path
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.
