Business Process Optimization with Reinforcement Learning

We investigate the use of deep reinforcement learning to optimize business processes in a business support system. The focus of this paper is to investigate how a reinforcement learning algorithm named Q-Learning, using deep learning, can be configured in order to support optimization of business processes in an environment which includes some degree of uncertainty. We make the investigation possible by implementing a software agent with the help of a deep learning tool set. The study shows that reinforcement learning is a useful technique for business process optimization but more guidance regarding parameter setting is needed in this area.