Hill Climbing: Fundamentals and Applications
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Hill climbing is a method of mathematical optimization that is used in numerical analysis. It is a member of the family of techniques known as local search. It is an iterative algorithm that begins with an arbitrary solution to a problem, and then seeks to discover a better answer by making incremental changes to the initial solution in order to see whether it leads to a better solution. If the change results in a better solution, then another incremental adjustment is made to the new solution, and so on and so forth, until there is no possibility of any further improvements being found.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Hill climbing
Chapter 2: Gradient descent
Chapter 3: Greedy algorithm
Chapter 4: Mean shift
Chapter 5: A* search algorithm
Chapter 6: Mathematical optimization
Chapter 7: Local search (optimization)
Chapter 8: Iterative method
Chapter 9: Travelling salesman problem
Chapter 10: Local optimum
(II) Answering the public top questions about hill climbing.
(III) Real world examples for the usage of hill climbing in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of hill climbing' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of hill climbing.
