Bio-inspired computing: constituents and challenges

Abstract

Nature has remedies for almost all problems. Though biological systems exhibits organised, complex and intelligent behaviour, they comprise of simple elements and governed by simple rules. Hence, mimicking such systems has been the attraction of researchers in the fields of computer science, neuroscience and biology for a long time. Generating complex behaviour from small agents working locally following simple rules is a highly cost-effective solution of the real life problem. Bio-inspired computing can be achieved through different models such as stochastic, ad hoc or discrete models; new paradigm inspired from nature like evolutionary approach and immune systems; and new platform, novel architecture and specially designed material such as artificial fuel cell. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing and quantum computing, etc. This article discusses consortium of bio-inspired computing along with applications and research scope. In spite of having advantages offered by partial simulation of natural intelligence, there are some limitations of the bio-inspired computing that need to be addressed. These challenges include creation of new model, techniques and platforms for bio-inspired computing. This article concludes with the challenges to be explored in the field.