Reinforcement Learning for Structural Control
نویسندگان
چکیده
منابع مشابه
Reinforcement Learning for Control
Reinforcement learning (RL) offers a principled way to control nonlinear stochastic systems with partly or even fully unknown dynamics. Recent advances in areas such as deep learning and adaptive dynamic programming (ADP) have led to significant inroads in applications from robotics, automotive systems, smart grids, game playing, traffic control, etc. This open track provides a forum of interac...
متن کاملReinforcement learning for robot control
Writing control code for mobile robots can be a very time-consuming process. Even for apparently simple tasks, it is often difficult to specify in detail how the robot should accomplish them. Robot control code is typically full of “magic numbers” that must be painstakingly set for each environment that the robot must operate in. The idea of having a robot learn how to accomplish a task, rather...
متن کاملReinforcement Learning for Elevator Control ?
Reinforcement learning (RL) comprises an array of techniques that learn a control policy so as to maximize a reward signal. When applied to the control of elevator systems, RL has the potential of finding better control policies than classical heuristic, suboptimal policies. On the other hand, elevator systems offer an interesting benchmark application for the study of RL. In this paper, RL is ...
متن کاملReinforcement Learning for Racecar Control
This thesis investigates the use of reinforcement learning to learn to drive a racecar in the simulated environment of the Robot Automobile Racing Simulator. Real-life race driving is known to be difficult for humans, and expert human drivers use complex sequences of actions. There are a large number of variables, some of which change stochastically and all of which may affect the outcome. This...
متن کاملReinforcement 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...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computing in Civil Engineering
سال: 2008
ISSN: 0887-3801,1943-5487
DOI: 10.1061/(asce)0887-3801(2008)22:2(133)