Biomimicry for Optimization, Control, and Automation

Springer-Verlag, London, UK, 2005

by: Kevin M. Passino

Synopsis:

• Part I: Introduction: Challenges of control and automation (appropriate for non-controls person), scientific foundations of biomimicry.
• Part II: Elements of Decision-Making: Neural network substrates for control instincts, rule-based control, planning systems, attentional systems (including stability analysis).
• Part III: Learning: Learning and control (off/on-line approximation perspective, heuristic adaptive control), linear least squares methods (batch and recrusive least squares), gradient methods (e.g. Levenberg-Marquardt), adaptive control (optimization perspective, introduction to stable adaptive control).
• Part IV: Evolution: Genetic algorithm, stochastic and nongradient optimization for design (e.g., pattern search methods, response surface methodology), evolution and learning: synergistic effects.
• Part V: Foraging: Cooperative foraging and search (optimization models, swarm stability), competitive and intelligent foraging (game-theoretic formulations, outlook on future of area).

Book Resources:

• Matlab code for book examples and homework problems
• Errata
• Exercises and Design Problems: At this link there are some hints and some additional problems.
• For a syllabus sample, click here.
• The lecture slides for the book are in three .pdf files:
  • ICcourse03-1.pdf (20MB)
  • ICcourse03-2.pdf (5MB)
  • ICcourse03-3.pdf (12MB)
• Laboratory: At OSU we have run a number of relevant laboratories over the years. Right now, the most relevant one is the Distributed Dynamical Systems Laboratory and the associated ECE 758 lab course.
• For some of my relevant publications, click here.
• For some of my relevant presentations, click here.

Ordering Information: See the Springer web page, or see Amazon.com by clicking here.

Features:

• 926 pages, 365 figures
• Homework exercises/design problems
• Many worked examples and applications
• Significant amount of Matlab code available (see above)

Table of Contents:

Preface

Part I: Introduction

Chapter 1: Challenges in Computer Control and Automation
Chapter 2: Scientific Foundations for Biomimicry
Chapter 3: For Further Study

Part II: Elements of Decision Making

Chapter 4: Neural Network Substrates for Control Instincts
Chapter 5: Rule-Based Control
Chapter 6: Planning Systems
Chapter 7: Attentional Systems
Chapter 8: For Further Study

Part III: Learning

Chapter 9: Learning and Control
Chapter 10: Linear Least Squares Methods
Chapter 11: Gradient Methods
Chapter 12: Adaptive Control
Chapter 13: For Further Study

Part IV: Evolution

Chapter 14: The Genetic Algorithm
Chapter 15: Stochastic and Nongradient Optimization for Design
Chapter 16: Evolution and Learning: Synergistic Effects
Chapter 17: For Further Study

Part V: Foraging

Chapter 18: Cooperative Foraging and Search
Chapter 19: Competitive and Intelligent Foraging
Chapter 20: For Further Study

Bibliography
Index

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