Imitation programming

Authors:
Larry Bull
Affiliations:
Department of Computer Science, University of the West of England, Bristol, UK
Venue:
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
Year:
2010

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Abstract

Many nature-inspired mechanisms have been presented for computational design and optimization. This paper introduces a population-based approach inspired by a form of cultural learning - imitation. Imitation is typically defined as learning through the copying of others. In particular, it is used in this paper to design simple circuits using a discrete dynamical system representation - Turing's unorganised machines. Initial results suggest the imitation computation approach presented is competitive with evolutionary computation, i.e., another class of stochastic population-based search, to design circuits from such recurrent NAND gate networks. Synchronous and asynchronous circuits are considered.