**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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