Coverart for item
The Resource Simulation-Based Optimization : Parametric Optimization Techniques and Reinforcement Learning, by Abhijit Gosavi, (electronic resource)

Simulation-Based Optimization : Parametric Optimization Techniques and Reinforcement Learning, by Abhijit Gosavi, (electronic resource)

Label
Simulation-Based Optimization : Parametric Optimization Techniques and Reinforcement Learning
Title
Simulation-Based Optimization
Title remainder
Parametric Optimization Techniques and Reinforcement Learning
Statement of responsibility
by Abhijit Gosavi
Creator
Author
Subject
Language
eng
Summary
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search, and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search, and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online), and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning, and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical, and computer), operations research, computer science, and applied mathematics.--
Member of
Assigning source
Provided by publisher
http://library.link/vocab/creatorName
Gosavi, Abhijit
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
0A7Id835zTI
Image bit depth
0
Literary form
non fiction
Nature of contents
dictionaries
Series statement
  • Operations Research/Computer Science Interfaces Series,
  • Springer eBooks.
Series volume
55
http://library.link/vocab/subjectName
  • Operations research
  • Decision making
  • Management science
  • Computer simulation
Label
Simulation-Based Optimization : Parametric Optimization Techniques and Reinforcement Learning, by Abhijit Gosavi, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=https://doi.org/10.1007/978-1-4899-7491-4
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Background -- Simulation basics -- Simulation optimization: an overview -- Response surfaces and neural nets -- Parametric optimization -- Dynamic programming -- Reinforcement learning -- Stochastic search for controls -- Convergence: background material -- Convergence: parametric optimization -- Convergence: control optimization -- Case studies
Control code
978-1-4899-7491-4
Dimensions
unknown
Edition
2nd ed. 2015.
Extent
1 online resource (XXVI, 508 pages)
File format
multiple file formats
Form of item
  • online
  • electronic
Governing access note
Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
Isbn
9781489974914
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-1-4899-7491-4
Other physical details
42 illustrations
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)1135574159
Label
Simulation-Based Optimization : Parametric Optimization Techniques and Reinforcement Learning, by Abhijit Gosavi, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=https://doi.org/10.1007/978-1-4899-7491-4
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Background -- Simulation basics -- Simulation optimization: an overview -- Response surfaces and neural nets -- Parametric optimization -- Dynamic programming -- Reinforcement learning -- Stochastic search for controls -- Convergence: background material -- Convergence: parametric optimization -- Convergence: control optimization -- Case studies
Control code
978-1-4899-7491-4
Dimensions
unknown
Edition
2nd ed. 2015.
Extent
1 online resource (XXVI, 508 pages)
File format
multiple file formats
Form of item
  • online
  • electronic
Governing access note
Use of this electronic resource may be governed by a license agreement which restricts use to the European University Institute community. Each user is responsible for limiting use to individual, non-commercial purposes, without systematically downloading, distributing, or retaining substantial portions of information, provided that all copyright and other proprietary notices contained on the materials are retained. The use of software, including scripts, agents, or robots, is generally prohibited and may result in the loss of access to these resources for the entire European University Institute community
Isbn
9781489974914
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-1-4899-7491-4
Other physical details
42 illustrations
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)1135574159

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