Biomimicry for Optimization, Control, and Automation [electronic resource] / by Kevin M. Passino.

Challenges in Computer Control and Automation -- Scientific Foundations for Biomimicry -- For Further Study -- Elements of Decision Making -- Neural Network Substrates for Control Instincts -- Rule-Based Control -- Planning Systems -- Attentional Systems -- For Further Study -- Learning -- Learning and Control -- Linear Least Squares Methods -- Gradient Methods -- Adaptive Control -- For Further Study -- Evolution -- The Genetic Algorithm -- Stochastic and Nongradient Optimization for Design -- Evolution and Learning: Synergistic Effects -- For Further Study -- Foraging -- Cooperative Foraging and Search -- Competitive and Intelligent Foraging -- For Further Study.

Biomimicry uses our scienti?c understanding of biological systems to exploit ideas from nature in order to construct some technology. In this book, we focus onhowtousebiomimicryof the functionaloperationofthe “hardwareandso- ware” of biological systems for the development of optimization algorithms and feedbackcontrolsystemsthatextendourcapabilitiestoimplementsophisticated levels of automation. The primary focus is not on the modeling, emulation, or analysis of some biological system. The focus is on using “bio-inspiration” to inject new ideas, techniques, and perspective into the engineering of complex automation systems. There are many biological processes that, at some level of abstraction, can berepresentedasoptimizationprocesses,manyofwhichhaveasa basicpurpose automatic control, decision making, or automation. For instance, at the level of everyday experience, we can view the actions of a human operator of some process (e. g. , the driver of a car) as being a series of the best choices he or she makes in trying to achieve some goal (staying on the road); emulation of this decision-making process amounts to modeling a type of biological optimization and decision-making process, and implementation of the resulting algorithm results in “human mimicry” for automation. There are clearer examples of - ological optimization processes that are used for control and automation when you consider nonhuman biological or behavioral processes, or the (internal) - ology of the human and not the resulting external behavioral characteristics (like driving a car). For instance, there are homeostasis processes where, for instance, temperature is regulated in the human body.