Floreano, Dario, and Claudio Mattiussi, Bio-Inspired Artificial Intelligence: The- ories, Methods an update through the likelihood p(T |w,I) of the prior pdf of the . Bio Inspired Artificial Intelligence Theories Methods. And Technologies Intelligent Robotics And. Let's read! We will often find out this sentence everywhere. Bio-Inspired Artificial Intelligence Theories, Methods, and Technologies Dario Floreano and Claudio Mattiussi. New approaches to artificial intelligence spring.

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PDF | On Sep 1, , Ivan I. Garibay and others published Dario Floreano and Claudio Mattiussi (eds): Bio-inspired artificial intelligence. Request PDF on ResearchGate | On Jan 1, , Dario Floreano and others published Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. PDF | Many objects and processes inspired by the nature have been recreated by the scientists. The inspiration to create a Multilayer Neural Network came from .

This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems--including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems.

Chapters end with a concluding overview and suggested reading. Get A Copy. Hardcover , pages.

More Details Original Title. Other Editions 1. Friend Reviews. To see what your friends thought of this book, please sign up. To ask other readers questions about Bio-Inspired Artificial Intelligence , please sign up. Be the first to ask a question about Bio-Inspired Artificial Intelligence.

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Showing Rating details. Sort order. Apr 22, Navid Asmari Saadabad rated it really liked it. A broad review of the various methods and instruments that have been used in multitudes of projects to create artificial intelligence.

Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies

Unlike most of the available textbooks that try to cover these intelligent methods, understanding the contents does not require a strong knowledge in computer science, physics, or biology. The formulations are presented in a very easy-to-comprehend method and the mathematical terms are fully explained upon their first appearance.

It can work both as a starter and as a detailed summarizing article. The textbook can be divided into two separate sections: It is not possible to follow the last two chapters selectively, unless the reader has a brief background in evolutionary algorithms, neural networks, and developmental systems which constitute the basic components of section 1.

Supplementary materials of the book including slides and exercises can be found at http: Nov 29, Mangoo rated it really liked it. A comprehensive textbook on its topic. Rather verbose, but well structured. Its scope is very broad and it may even appear pretentious, as entire books can be written on each of its 7 chapters. Each chapter is nonetheless quite long, introduces the topic with a gradual progression of details and sophistications, and surveys most of the relevant work done in the field up to In addition, it provides a rather vast set of references to further dig all topics and related material, and sometim A comprehensive textbook on its topic.

In addition, it provides a rather vast set of references to further dig all topics and related material, and sometimes boxes are introduced and dedicated to selected, multi-disciplinary topics.

In short, a precious book for people interested in this huge, expanding if sometime abused field. Sep 20, Dav rated it really liked it. Probably the best biology book I've read. Since it is targeted at AI engineers such that each examination of a biological system is followed by engineering applications, it uses a systems-oriented explanatory approach which I found easier to follow than the usual biologist-targeted text.

The section on the immune system was fascinating! It is hard to imagine another book on this subject that could cover the breadth and depth any better. I need to check it out one more time to finish the last two Probably the best biology book I've read.

I need to check it out one more time to finish the last two sections, but I've read enough to heartily recommend it to any comsci people who are looking for broad yet detailed survey of this space. Sep 21, Michiel rated it really liked it Shelves: A very interesting book! Discusses some of the most important fields in and methods in AI with the complexity in biology as a red line from methods inspired by evolution, to cells, to development ending with behaviour of groups of organisms.

Not very heavy on its math, basic high-school calculus would suffice to understand most conc A very interesting book! Not very heavy on its math, basic high-school calculus would suffice to understand most concepts in some detail.

Joel rated it it was amazing Nov 13, Adam Elkus rated it really liked it Aug 25, Google Scholar Dorigo, M. Ant system: Optimization by a colony of cooperating agents.

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SANS Industrial control system. Analysis of the cyber attack on the ukrainian power grid, March Google Scholar Firdaus, A. Bio-inspired computational paradigm for feature investigation and malware detection: Interactive analytics. Multimedia Tools and Applications, 1— Google Scholar Fister, I. A brief review of nature-inspired algorithms for optimization.

Bio-inspired artificial intelligence: Theories, methods, and technologies. Cambridge: MIT press. Google Scholar Forrest, S.

Self-nonself discrimination in a computer. In Research in security and privacy, Google Scholar Fu, J. Introducing adjuvants to dendritic cell algorithm for stealthy malware detection.

Google Scholar Gonsalves, T. Two diverse swarm intelligence techniques for supervised learning. In Psychology and mental health: Concepts, methodologies, tools, and applications pp. IGI Global.

Google Scholar Hlaing, Z. An ant colony optimization algorithm for solving traveling salesman problem. International Conference on Information Communication and Management, 16, 54— Google Scholar Holland, J. Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control and artificial intelligence. Ann Arbor: University of Michigan Press. Epidemic algorithms, Universitat Paderborn, Algorithms of the Internet presentation.

Google Scholar Hu, H.

WiFi networks and malware epidemiology. Proceedings of the National Academy of Sciences, 5 , — Adversarial machine learning. In Proceedings of the 4th ACM workshop on security and artificial intelligence pp. Google Scholar Iima, H. Swarm reinforcement learning algorithm based on particle swarm optimization whose personal bests have lifespans.

In International conference on neural information processing pp. A quantitative measure of fairness and discrimination for resource allocation in shared computer system Vol.

Google Scholar Jerne, N. Towards a network theory of the immune system. Annales d'immunologie, , Google Scholar Kantarcioglu, M. Adversarial data mining: Big data meets cyber security.

Google Scholar Kar, A.

Bio-Inspired Artificial Intelligence

Bio inspired computing—A review of algorithms and scope of applications. Expert Systems with Applications, 59, 20— The spread of wi-fi router malware revisited. In 20th communications and networking simulation symposium CNS Google Scholar Kennedy, J. Particle swarm optimization. In Neural Networks, Google Scholar Kim, S.

Cognitive radio anti-jamming scheme for security provisioning iot communications. Syst, 9, — Google Scholar Kolias, C. Swarm intelligence in intrusion detection: A survey.

Termid: A distributed swarm intelligence-based approach for wireless intrusion detection. International Journal of Information Security, 16 4 , 1— Google Scholar Labib, M. A colonel blotto game for anti-jamming in the internet of things. Google Scholar Linkov, I. Resilience metrics for cyber systems.

Environment Systems and Decisions, 33 4 , — Modeling the propagation of mobile malware on complex networks. Communications in Nonlinear Science and Numerical Simulation, 37, — Tolerance, danger, and the extended family. Annual Review of Immunology, 12 1 , — Jamming in the internet of things: A game-theoretic perspective.

In I. Google Scholar Neumann, F. In Bioinspired computation in combinatorial optimization: Algorithms and their computational complexity pp. Distributed routing in wireless sensor networks using energy welfare metric.

Information Sciences, 9 , — Resilient design methodology for cyber-physical systems. Google Scholar Parpinelli, R. Data mining with an ant colony optimization algorithm.Nazmul Ahmed Noyon rated it really liked it Aug 04, Syst, 9, — Sep 20, Dav rated it really liked it.

Nov 29, Mangoo rated it really liked it. Towards a network theory of the immune system. International Journal of Information Security, 16 4 , 1—

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