Modelling and Training Unconventional in-Materio Computers using Bio-Inspired Techniques - Research Database, The University of York

By the same authors

A substrate-independent framework to characterize reservoir computers
Dale, M., Miller, J. F., Stepney, S. & Trefzer, M. A., 19 Jun 2019
Article in Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences
A Substrate-Independent Framework to Characterise Reservoir Computers
Dale, M., Miller, J. F., Stepney, S. & Trefzer, M. A., 19 Jun 2019
Article in Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
A Substrate-Independent Framework to Characterise Reservoir Computers
Dale, M., Miller, J. F., Stepney, S. & Trefzer, M. A., 16 Oct 2018, arXiv, 19 p.
Research output: Working paper
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Dale, M. N., Miller, J. F., Stepney, S. & Trefzer, M. A., 2017.
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Research output: Contribution to conference › Paper

Modelling and Training Unconventional in-Materio Computers using Bio-Inspired Techniques

Research output: Contribution to conference › Poster

Author(s)

Department/unit(s)

Conference

Conference	15th International Conference on Artificial Life (ALife)
Country	Mexico
City	Cancun
Conference date(s)	4/07/16 → …

Publication details

Date	Published - Jul 2016
Number of pages	12
Original language	English

Research areas

evolution in materio, evolutionary computation, carbon nano tubes, unconventional computing

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