We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
In this article, we propose a method to adapt stepsize parameters used in reinforcement learning for dynamic environments. In general reinforcement learning situations, a stepsize...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
This paper presents the recognition of handwritten Hindi Characters based on the modified exponential membership function fitted to the fuzzy sets derived from features consisting...
Madasu Hanmandlu, O. V. Ramana Murthy, Vamsi Krish...