Liquid State Machines: Motivation, Theory, and Applications

Computability in Context, pp. 275-296 (2011) No AccessLiquid State Machines: Motivation, Theory, and ApplicationsWolfgang MaassWolfgang MaassInstitute for Theoretical Computer Science, Graz University of Technology, A-8010 Graz, Austriahttps://doi.org/10.1142/9781848162778_0008Cited by:60 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Abstract: The Liquid State Machine (LSM) has emerged as a computational model that is more adequate than the Turing machine for describing computations in biological networks of neurons. Characteristic features of this new model are (i) that it is a model for adaptive computational systems, (ii) that it provides a method for employing randomly connected circuits, or even “found” physical objects for meaningful computations, (iii) that it provides a theoretical context where heterogeneous, rather than stereo typical, local gates, or processors increase the computational power of a circuit, (iv) that it provides a method for multiplexing different computations (on a common input) within the same circuit. This chapter reviews the motivation for this model, its theoretical background, and current work on implementations of this model in innovative artificial computing devices. 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