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Algorithms for Optimization, Second Edition - by Mykel J Kochenderfer & Tim A Wheeler (Hardcover)

Name: Algorithms for Optimization, Second Edition - by Mykel J Kochenderfer & Tim A Wheeler (Hardcover)
Brand: MIT Press
SKU: 1011823930
Price: 115.99 USD
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Highlights

A comprehensive, practical introduction to optimization updated with new chapters on duality, quadratic programming, and disciplined convex programming.
About the Author: Mykel J. Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University, where he is the director of the Stanford Intelligent Systems Laboratory (SISL), author of Decision Making Under Uncertainty, and coauthor of Algorithms for Validation and Algorithms for Decision Making, all published by the MIT Press.
634 Pages
Computers, Artificial Intelligence

Description

Book Synopsis

A comprehensive, practical introduction to optimization updated with new chapters on duality, quadratic programming, and disciplined convex programming.

The extensively updated second edition of this popular textbook provides a comprehensive introduction to optimization with a focus on practical algorithms. Mykel Kochenderfer and Tim Wheeler approach optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. Suitable for advanced undergraduates and graduate students in mathematics, statistics, computer science, engineering, and operations research and as a reference for professionals, the text provides concrete implementations in the Julia programming language.

Second edition highlights:

New chapters on duality, quadratic programming, and disciplined convex programming
Additional methods covered, from new ways to estimate gradients to multifidelity techniques
Improved accessibility, expanded explanations, updated references, and streamlined algorithms
More exercises, example applications, and figures

About the Author

Mykel J. Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University, where he is the director of the Stanford Intelligent Systems Laboratory (SISL), author of Decision Making Under Uncertainty, and coauthor of Algorithms for Validation and Algorithms for Decision Making, all published by the MIT Press.

Tim A. Wheeler is a software engineer in the Bay Area, working on autonomy, controls, and decision-making systems. He is coauthor of Algorithms for Decision Making (MIT Press).

Specifications

Dimensions (Overall): 9.0 Inches (H) x 8.0 Inches (W)

Weight: 1.25 Pounds

Suggested Age: 22 Years and Up

Number of Pages: 634

Genre: Computers

Sub-Genre: Artificial Intelligence

Publisher: MIT Press

Theme: General

Format: Hardcover

Author: Mykel J Kochenderfer & Tim A Wheeler

Language: English

Street Date: January 5, 2027

TCIN: 1011823930

UPC: 9780262058162

Item Number (DPCI): 247-31-3774

Origin: Made in the USA or Imported

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