Download Bio-Inspired Artificial Intelligence: Theories, Methods, and by Dario Floreano, Claudio Mattiussi PDF

By Dario Floreano, Claudio Mattiussi

A finished creation to new methods in man made intelligence and robotics which are encouraged through self-organizing organic procedures and structures.

Traditionally synthetic intelligence has been all for trying to reflect the cognitive skills of the human mind. substitute techniques to man made intelligence take concept from a much broader diversity of organic methods reminiscent of evolution, networks of neurons and studying. In fresh a long time there was an explosion of recent man made intelligence tools encouraged via much more organic methods, similar to the immune procedure, colonies of ants, actual embodiment, improvement, coevolution, self-organization, and behavioral autonomy, to say quite a few. ‘‘Bio-Inspired synthetic Intelligence: Theories, tools, and Technologies’’, by means of Dario Floreano and Claudio Mattiussi, is a scientific and entire creation to the rising box that teams these kind of tools: biologically encouraged synthetic intelligence. for this reason, it discusses organic and synthetic platforms that function at quite a lot of time and house scales, yet manages to maneuver fluently from sluggish evolutionary time, to life-time studying, to genuine time model. at the house scale, it is going from person cells and neurons, to multicellular organisms, and all of the strategy to societies. i discovered this e-book extraordinary for a minimum of purposes. First, it offers a coherent highbrow framework to arrange most of these computational advancements by way of grounding them of their organic nature and within the pervasiveness of evolution all through biology. moment, it presents a transparent, wellwritten, accomplished, and authoritative account of those advancements in a tutorial structure well matched for a school room. The authors be ready to do all of that during merely 659 pages, an exceptional accomplishment contemplating the scope and intensity of this e-book. The e-book is geared up in seven chapters: evolutionary platforms, mobile structures, neural platforms, developmental platforms, immune structures, behavioral structures and collective platforms. The chapters aren't autonomous yet intended to be learn so as

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Extra resources for Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies (Intelligent Robotics and Autonomous Agents series)

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Since it is impossible to sample all possible individuals for any realistic problem, in practice one considers a few hundred or thousand genotypes generated by randomly sampling the genetic representation. For the sake of visualization, often fitness landscapes are collapsed to a two-dimensional graph where all sampled individuals are lined on the same axis according to some ordering criterion (for example, string distance or sampling order). If most of the fitness values are equal or zero, the evolvability of the system is very low.

Another problem is that the dimension of the search space and the number of possible solutions is predefined and constant, which limits the potential of generating more complex solutions over generations. Despite all these caveats, evolutionary algorithms in computer science and engineering often resort to variations of the three genetic representations that have been described in this section because they work reasonably well for a large number of function optimization problems. The issue of evolvability and of more suitable genotype-phenotype mappings typically arises when one is interested in evolving phenotypes made of several different components, such as complex electronic devices or autonomous robots, or when one is interested in open-ended evolution.

Engineers at NASA took advantage of this rapid redesign feature when it was decided that the planned nanosatellites would orbit at a different orientation and altitude and thus require a new antenna design. 13 CIRCUIT TOPOLOGY CIRCUIT SIZING Evolutionary Electronics We devote the remaining part of this chapter to evolutionary electronics, that is, to the application of the evolutionary approach to the design of electronic circuits. By electronic circuit we mean a collection of interconnected electronic devices such as transistors, resistors, and logic gates.

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