Differential dynamic programming: Difference between revisions

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Revision as of 04:45, 15 August 2020

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Sampled differential dynamic programming has been extended to Path Integral Policy Improvement with Differential Dynamic Programming.<ref>{{Cite journal|last=Lefebvre|first=Tom|last2=Crevecoeur|first2=Guillaume|date=July 2019|title=Path Integral Policy Improvement with Differential Dynamic Programming|url=https://ieeexplore.ieee.org/abstract/document/8868359|journal=2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)|pages=739–745|doi=10.1109/AIM.2019.8868359|hdl=1854/LU-8623968|hdl-access=free}}</ref> This creates a link between differential dynamic programming and path integral control,<ref>{{Cite journal|last=Theodorou|first=Evangelos|last2=Buchli|first2=Jonas|last3=Schaal|first3=Stefan|date=May 2010|title=Reinforcement learning of motor skills in high dimensions: A path integral approach|url=https://ieeexplore.ieee.org/document/5509336|journal=2010 IEEE International Conference on Robotics and Automation|pages=2397–2403|doi=10.1109/ROBOT.2010.5509336}}</ref> which is a framework of stochastic optimal control.

== Constrained problems ==

Interior Point Differential dynamic programming (IPDDP) is an [[interior-point method]] generalization of DDP that can address the optimal control problem with nonlinear state and input constraints. <ref>{{cite arXiv |last=Pavlov |first=Andrei|last2=Shames|first2=Iman| last3=Manzie|first3=Chris|date=2020 |title=Interior Point Differential Dynamic Programming |eprint=2004.12710 |class=math.OC}}</ref>

== See also ==