Nature has evolved ways to solve many kinds of complex problems. Investigating these natural ‘solutions’ is a fruitful source of insights about the nature of complexity, and about ways to manage complex systems. Increasingly it is apparent that instead of trying to design complex systems it is often better to build systems that can evolve into robust designs. For example, evolutionary methods can produce adequate solutions to many problems of scheduling and optimisation that are intractable by traditional means. The spread of information technology throughout society has made the idea of natural computation (treating biological processes as forms of computing) increasingly influential. Evolution has inspired a host of new ideas in computing. The ideas of adaptation and evolution are crucial in emerging new computing-based technologies such as multi-agent systems, genetic regulatory networks and virtual reality. Every age tends to see the world in terms of its preoccupations. During the Industrial Revolution, science treated the world as a great machine. Today, in the midst of an information revolution, an increasingly fruitful paradigm is to view nature as a form of computation. This new paradigm, widely known as Natural Computation, has not only provided many new insights about living systems, but has also proved to be one of the most productive and fruitful areas of computing.
|Title of host publication||Pragmatic Evolution: Applications of Evolutionary Theory|
|Place of Publication||New York NY USA|
|Publisher||Cambridge University Press|
|Pages||213 - 233|
|Number of pages||21|
|Publication status||Published - 2012|