Intelligent Inventory Control via Ruminative Reinforcement Learning

Ruminative Reinforcement Learning: Improve Intelligent Inventory Control by Ruminating on the Past

Reinforcement Learning (RL) can solve practical sequential decision problems, even when structures of the problems are less understood. However, some sequential decision problems intrinsically have structural parts that are easily to formulate and distinguish from less understood parts. Exploiting this knowledge may help improve performance of RL. This study proposed and investigated an approac...

Advances in Reinforcement Learning and Their Implications for Intelligent Control

Mobile Agent Control in Intelligent Space using Reinforcement Learning

Finding the safest shortest path in an unknown environment is a fundamental task in mobile robotics. To emulate the human adaptibility in this field, we can use the Intelligent Space concept. The Intelligent Space is a distributed sensory system, which is the background infrastructure to observe human walking in a limited area. The observation of human beings is applied to create a walkable are...

Learning to control dynamic systems via associative reinforcement learning

and the lack of explicit instructional information about how to perform a given control task. Under these circumstances, techniques developed by arti cial intelligence researchers for \learning from examples," including the \supervised learning" techniques studied by neural network researchers, are not directly applicable because these techniques are based on the availability of training inform...

Reinforcement Learning Based PID Control of Wind Energy Conversion Systems

In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability an...