With the evolution of our complex technological society and the introduction of new notions and innovative theoretical tools in the field of intelligent systems, the field of neural networks is undergoing an enormous evolution. These evolving and innovative theoretical tools are centered around the theory of soft computing, a theory that embodies the theory from the fields of neural networks, fuzzy logic, evolutionary computing, probabilistic computing, and genetic algorithms. These tools of soft computing are providing some intelligence and robustness in the complex and uncertain systems similar to those seen in natural biological species.
Intelligence — the ability to learn, understand, and adapt — is the creation of nature, and it plays a key role in human actions and in the actions of many other biological species. Humans possess some robust attributes of learning and adaptation, and that's what makes them so intelligent. We humans react through the process of learning and adaptation on the information received through a widely distributed network of sensors and control mechanisms in our bodies. The faculty of cognition — which is found in our carbon-based computer, the brain — acquires information about the environment through various natural sensory mechanisms such as vision, hearing, touch, taste, and smell.