Learning Decision Sequences for Repetitive Processes--Selected Algorithms
Title Statements
- Full title :Learning Decision Sequences for Repetitive Processes--Selected Algorithms
Edition Statements
- Publication Date:2021.
Publication Statements
- Publisher(s):Springer International Publishing AG
- Place of Publication:Cham
- Language:eng
- Publication Date:2021.
Notes
Description based upon print version of record.
6.3 Response Surface Methodology for Searching for the Optimum.
The Physical Object
- Description:1 online resource (132 p.).
Edition Identifiers
- ISBN:9783030883966, 3030883965
- oclc:on1285781373
- LC Classification:TA1-2040
Table of Contents
Intro -- Contents -- List of Figures -- List of Tables -- 1 Introduction -- 2 Basic Notions and Notations -- 2.1 Repetitive Processes -- 2.1.1 Process States -- 2.1.2 States of Repetitive Processes -- 2.2 Decision Sequences and Disturbances -- 2.2.1 Univariate Decision Sequences -- 2.2.2 Multivariable Decision Sequences -- 2.2.3 Random Disturbances -- 2.2.4 Decision Making and Implementation -- 2.3 Static Models of Processes and Loss Functions -- 2.3.1 Model-Based Versus Model-Inspired Approaches -- 2.3.2 Deterministic Static Models -- 2.3.3 Probabilistic Static Models
2.3.4 Assessing the Quality of Decision Sequences -- 2.3.5 Illustrative Example -- 2.4 Models of Dynamic Processes -- 2.4.1 Markov Chains Models -- 2.4.2 Deterministic Models and Miscellaneous Remarks -- 2.4.3 Quality Criteria for Dynamic Processes -- 3 Learning Decision Sequences and Policies for Repetitive Processes -- 3.1 Learning Decisions and Decision Sequences -- 3.1.1 Remarks on Learning in Control Systems -- 3.1.2 Selected Learning Tasks in Operations Research -- 3.2 How Algorithms Can Learn -- 3.2.1 Learning directly from a static process I -- 3.2.2 Learning by stochastic approximation
3.2.3 Remarks on mo…
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Rate & Review