17 citations · 40 across the 10 of their papers we have counts for
4 papers · 1 filter
Online variants of the cross-entropy method
Istvan Szita, Andras Lorincz
The cross-entropy method is a simple but efficient method for global optimization. In this paper we provide two online variants of the basic CEM, together with a proof of convergen…
Low-complexity modular policies: learning to play Pac-Man and a new framework beyond MDPs
Istvan Szita, Andras Lorincz
In this paper we propose a method that learns to play Pac-Man. We define a set of high-level observation and action modules. Actions are temporally extended, and multiple action mo…
Reinforcement Learning with Linear Function Approximation and LQ control Converges
Istvan Szita, Andras Lorincz
Reinforcement learning is commonly used with function approximation. However, very few positive results are known about the convergence of function approximation based RL control a…
Kalman filter control in the reinforcement learning framework
Istvan Szita, Andras Lorincz
There is a growing interest in using Kalman-filter models in brain modelling. In turn, it is of considerable importance to make Kalman-filters amenable for reinforcement learning.…