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Speaker(s): Dr Richard A Watson
Organiser: Dr David Millard
Time: 15/11/2004 12:50-13:40
Location: B67/1027

Abstract

Conventionally, evolution by natural selection is almost inseparable from the notion of accumulating successive slight variations. Notions of gradualism are deeply ingrained in evolutionary thought and strongly influence our ideas about what kinds of systems are evolvable and which are not. The very idea of large adaptive genetic changes is considered unevolutionary. Indeed, attacking the plausibility of a linear gradual succession of proto-systems is a common form of criticism for evolutionary theory from Paley (1802) to Behe (1996), and asserting the plausibility of a gradual succession of proto-systems is a common form of defence (Dawkins 1996). But is gradualism the only valid framework for evolution by natural selection?

Darwin's masterful contribution was to provide an algorithmic model of how adaptation may take place in biological systems. However, the hill-climbing algorithm that he described - the sequential linear accumulation of successive slight modifications - is only one algorithmic possibility. In this work I show that compositional evolution, utilising mechanisms such as sexual recombination and symbiotic encapsulation, do not fit within the hill-climbing framework and provide a fundamentally distinct form of adaptational process allied to divide-and-conquer problem decomposition. Since compositional evolution does not operate within the hill-climbing framework, gradualist notions of evolutionary difficulty do not apply.

Accordingly, I am able to show that certain kinds of complex systems are in principle easily evolvable under compositional evolution despite the abscence of a gradual succession of proto-systems.

Presentation Links

Richard Watson Homepage

Speaker Biography

Dr Richard A. Watson

With a background in computer science from Sussex University, UK, and Brandeis University, USA, Richard pursued interests in the interface between evolutionary computation and evolutionary biology at Harvard University, USA. He is now a lecturer in Computer Science, working at the interface with the life sciences, at Southampton University, UK.