Abstract:

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.

@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
)