Imitation programming

Bull, Larry

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. © 2010 Springer-Verlag Berlin Heidelberg.

Citation

Bull, L. (2010). Imitation programming. Lecture Notes in Artificial Intelligence, 6274 LNCS, 360-371. https://doi.org/10.1007/978-3-642-15323-5_31

• Journal Article Type: Conference Paper
• Publication Date: Nov 8, 2010
• Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
• Print ISSN: 0302-9743
• Electronic ISSN: 1611-3349
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 6274 LNCS
• Pages: 360-371
• Series Title: Lecture Notes in Computer Science
• DOI: https://doi.org/10.1007/978-3-642-15323-5_31
• Keywords: softwaqre engineering, computation by abstract devices, computer communication networks, artificial intelligence, AI, logics and meanings of programs, special purpose and application based systems
• Public URL: https://uwe-repository.worktribe.com/output/983779
• Publisher URL: http://www.springerlink.com