Computer simulation of heuristic reinforcement-learning systems for nuclear power plant load changes control

Abstract

This paper describes two ideas and sample simulation results of a heuristic reinforcement-learning system and its application to the problem of digital computer control of a simple nuclear plant model. The idea of the system is interconnection between the well known reactor control heuristic rules [8,9], and the reinforcement learning algorithms [4,5]. The control signal is proposed as a vector depending on complex physical properties of the plant. Such an approach is far more flexible than deterministic or stochastic techniques when dealing with unknown processes and novel control situations.