Research in substrate-based computing has shown that materials contain rich properties that can be exploited to solve computational problems. One such technique known as Evolution-in-materio uses evolutionary algorithms to manipulate material substrates for computation. However, in general, modelling the computational processes occurring in such systems is a difficult task and understanding what part of the embodied system is doing the computation is still fairly ill-defined. This chapter discusses the prospects of using Reservoir Computing as a model for in materio computing, introducing new training techniques (taken from Reservoir Computing) that could overcome training difficulties found in the current Evolution-in-Materio technique.
doi:10.1007/978-3-319-33924-5_22 | full chapter PDF
@inproceedings(Dale-AdvUComp-2017, author = "Matthew Dale and Julian F. Miller and Susan Stepney", title = "Reservoir Computing as a Model for {\it In Materio} Computing", pages = "533-571", crossref = "AdvUComp-2017" ) @proceedings(AdvUComp-2017, editor = "Andrew Adamatzky", title = "Advances in Unconventional Computing, vol 1", booktitle = "Advances in Unconventional Computing, vol 1", publisher = "Springer", year = 2017 )