An Integrated Design Method using Reinforcement Learning Model

DOI

10.2991/icemct-15.2015.226How to use a DOI?

Keywords

reinforcement learning (RL), design, method, application

Abstract

This is followed by a summary of future research directions, and possibilities for technology transition that are currently underway. RL can autonomously get optional policy with the knowledge obtained by trial-and-error and continuously interacting with dynamic environment. Firstly, the model and theory of reinforcement learning is given. Then, a description of the controller architecture and associated stability analysis is given, followed by a more in-depth look at its application to a tiltrotor aircraft.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yingjun Hao
AU  - Shaosong Wan
AU  - Jian Cao
AU  - Cong Yan
PY  - 2015/06
DA  - 2015/06
TI  - An Integrated Design Method using Reinforcement Learning Model
BT  - Proceedings of the 2015 International Conference on Education, Management and Computing Technology
PB  - Atlantis Press
SP  - 1073
EP  - 1076
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemct-15.2015.226
DO  - 10.2991/icemct-15.2015.226
ID  - Hao2015/06
ER  -