Development of Control Strategies via Artificial Neural Networks and Reinforcement Learning

Artificial neural networks have been proposed as tools for process control. Reinforcement learning is one method of adjusting the weights on the connections in such a network to achieve the desired mapping for control action. We describe how reinforcement learning can be viewed as just another optimization strategy, and propose an algorithm for learning that is based on an old direct search strategy.