Artificial intelligence and new approaches to this idea emerges from development, cells, bodies and societies as it does from evolution. It is more concerned with the abilities of human beings to reproduce and the capability of self-organization. Bio-robotics, swarm intelligence, immune systems, artificial neural networks are some of the examples of the new approaches in bio-inspired intelligence.
To develop new engineering solutions in the area of IT, biologically inspired computing has been introduced as a new scientific discipline that applies biological principles to the solutions. These solutions are based on the application of existing mechanisms in the nature for designing self-organized networks and systems that combines the knowledge of different branches of biology, mathematics and computer science.
Swarm Intelligence is defined as a combined behavior of self-organized, natural or artificial systems. Intelligent global behavior emerges from the interaction among population of simple agents and proper reasoning based on the information available. Some behavioral rules exploit local or network based information that users exchange via social networking or directly.
Bio-inspired computing quite differs from the traditional artificial intelligence as in it takes more revolutionary approach towards learning as compare to what defines a creationist used in traditional artificial intelligence. In traditional artificial intelligence the programmer is basically the creator who creates something and diffuses it with intelligence. A bio-inspired technique specifies a simple set of rules and organisms which to such rules and methods that apply those rules iteratively.
During the past few years bio-inspired computing has set a vogue as it claims that it does not contain the sense of delivering guaranteed performance in their domains that are clearly defined. But bio-inspired algorithms have a great ability to exhibit strength through their flexibility. Often when the task that is desired is not properly done, bio-inspired algorithms work very well and mainly adopt to unseen changes in the environment of the task.
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