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Topics in Convex Optimization for Optimal Control and Reinforcement Learning.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Topics in Convex Optimization for Optimal Control and Reinforcement Learning./
作者:	Kim, Jong.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	97 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-05, Section: A.
Contained By:	Dissertations Abstracts International83-05A.
標題:	Heat transfer. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28688307
ISBN:	9798544204114

Topics in Convex Optimization for Optimal Control and Reinforcement Learning.
Kim, Jong.

Topics in Convex Optimization for Optimal Control and Reinforcement Learning. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 97 p.

Source: Dissertations Abstracts International, Volume: 83-05, Section: A.

Thesis (Ph.D.)--Stanford University, 2021.

This item must not be sold to any third party vendors.

Optimal control describes the problem of finding a control to minimize an objective function for a dynamical system over a period of time. It has been applied in a wide variety of applications in robotics, signal processing, and machine learning over several decades. On the other hand, reinforcement learning (RL) assumes the uncertain model of transition dynamics and has achieved great empirical success in recent years including simulated game scenarios and robotics. This thesis focuses on topics in both optimal control and reinforcement learning.

ISBN: 9798544204114Subjects--Topical Terms:

3391367
Heat transfer.

Topics in Convex Optimization for Optimal Control and Reinforcement Learning.
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