DOI: 10.4018/978-1-4666-3646-0.ch001
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This chapter presents an introductory overview of the application of computational intelligence in biometrics. Starting with the historical background on artificial intelligence, the chapter proceeds to the evolutionary computing and neural networks. Evolutionary computing is an ability of a computer system to learn and evolve over time in a manner similar to humans. The chapter discusses swarm intelligence, which is an example of evolutionary computing, as well as chaotic neural network, which is another aspect of intelligent computing. At the end, special concentration is given to a particular application of computational intelligence—biometric security.
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1. A Historical Look At Artificial Intelligence

Over the course of the human history, the greatest minds: scientists, philanthropists, educators, politicians, leaders, philosophers, were fascinated with the way human brain works. From Michelangelo to Lomonosov, from DaVinci to Einstein, there have been numerous attempts to uncover the mystery of human mind and to replicate its working first through simple mechanical devices and later, in the 20th century, through computing machines and intelligent software.

In Alan Turing’s groundbreaking work “Computing Machinery and Intelligence,” he posed the question “Can machines think?” (Turing, 1950). In order to establish credible criteria to answer this question, he proposed a test, now well known as “The Turing Test” – to estimate a machine’s ability to demonstrate intelligence. The test is based on a conversation in a natural language between the human judge and the opponent, who can be either human or a machine. Judging by the answers, the judge must distinguish the machine from the human. If the judge fails to do so, the machine is deemed to have passed the test.

After the theoretical platform for an Automated Turing Test (ATT) was developed by Naor in 1996 (Naor, 1996), the new generation of researchers continued to study the same concept of human/machine identification. In addition to ATT, the new developed procedures were “Reversed Turing Test” (RTT); “Human Interactive Proof” (HIP); “Mandatory Human Participation” (MHP); and the “Completely Automated Public Turing Test to tell Computers and Humans Apart” (CAPTCHA) (Ahn, Blum, Hopper, & Langford, 2003).

In the modern terms, the Turing test could be considered as one of the behavioral biometrics, whereas the behavior is based on the literary responses to the questions. Another groundbreaking work in modern artificial intelligence was laid out by John von Neumann in the 1950's in his theory of automata and self-replicating machines, later published as a book (von Neumann, 1966). His theoretical concepts were based on those of Alan Turing.

Self-replication is a natural process which lies at the base of biological life cycle on Earth. At the core of self-replication of living organisms lies the biological fact that nucleic acids produce copies of themselves under proper conditions (Craig, Cohen-Fix, Green, Greider, Storz, & Wolberger, 2011). Self-replication in non-biological contexts has been studied only recently in the context of “artificial” entities such as self-replicating software, computer viruses, and robots (Gavrilova & Yampolskiy, 2011). The research has been fruitful in the past decade. Cornell University, Canada researchers have created a machine that can build copies of itself. Their robots are made up of a series of modular cubes (called “molecubes”), each containing identical parts and the computer program for replication. The cubes can change their topology by selectively attaching and detaching from each other using implanted magnets, where a complete robot is made up of a number of cubes connected together (Zykov, Mytilinaios, Adams, & Lipson, 2005).


2. Evolutional Computing And Neural Networks

Another approach taken in the same direction has led to a concept of evolutionary computing. The concept exploited here is ability of computer software to learn and evolve over time, similarly to how human learns, from experiences, facts and by example. The ability to develop winning strategies and improve itself comes as a natural, even so sometimes surprising result.

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