Aimsof traditional planners had beenlimited to finding a sequenceof operators rather than finding an optimal or neax-optimalfinal state. Consequent]y, the performanceimprovementsy...
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...
In this document we cany out a comparative analysis of the reasoning strategies implemented in Fuzzy Logic Controllers (hereinafter FLCs) and Faded Temporal Fuzzy Logic Controller...