Evolution-in-materio: Solving function optimization problems using materials

2014 14th UK Workshop on Computational Intelligence, UKCI 2014 - Proceedings

Volumn , Issue , 2014, Pages

  Mohid, Maktuba ^a   Miller, Julian F ^a   Harding, Simon L ^a   Tufte, Gunnar ^b   Lykkebo, Odd Rune ^b   Massey, Mark K ^c   Petty, Michael C ^c  

^a UNIVERSITY OF YORK   (United Kingdom)

^b NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^c DURHAM UNIVERSITY   (United Kingdom)

Author keywords

evolution in materio; evolutionary algorithm; evolvable hardware; function optimization; material computation

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; EVOLUTIONARY ALGORITHMS;

ARTIFICIAL EVOLUTION; COMPUTATIONAL PROBLEM; EVOLUTION-IN-MATERIO; EVOLUTIONARY APPROACH; EVOLVABLE HARDWARE; FUNCTION OPTIMIZATION; FUNCTION OPTIMIZATION PROBLEMS; HARDWARE PLATFORM;

INTELLIGENT COMPUTING;

EID: 84912127250     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/UKCI.2014.6930152     Document Type: Conference Paper

References (20)

1. Banzhaf, W., Beslon, G., Christensen, S., Foster, J., Képés, F., Lefort, V., Miller, J.F., Radman, M., Ramsden, J.: Guidelines: From artificial evolution to computational evolution: a research agenda. Nature Reviews Genetics 7, 729-735 (2006
2. Broersma, H., Gomez, F., Miller, J.F., Petty, M., Tufte, G.: NASCENCE Project: Nanoscale Engineering for Novel Computation Using Evolution. International Journal of Unconventional Computing 8(4), 313-317 (2012
3. Clegg, K.D., Miller, J.F., Massey, M.K., Petty, M.C.: Travelling salesman problem solved 'in materio' by evolved carbon nanotube device. In: Parallel Problem Solving from Nature-PPSN XIII-13th International Conference, Proceedings, LNCS, vol. 8672, pp. 692-701. Springer (2014
4. Harding, S., Miller, J.F.: Evolution in materio: A tone discriminator in liquid crystal. In: In Proceedings of the Congress on Evolutionary Computation 2004 (CEC'2004), vol. 2, pp. 1800-1807 (2004
5. Harding, S., Miller, J.F.: Evolution in materio : A real time robot controller in liquid crystal. In: Proceedings of NASA/DoD Conference on Evolvable Hardware, pp. 229-238 (2005
6. Harding, S., Miller, J.F.: Evolution in materio. In: R.A. Meyers (ed.) Encyclopedia of Complexity and Systems Science, pp. 3220-3233. Springer (2009
7. Harding, S.L., Miller, J.F.: Evolution in materio: Evolving logic gates in liquid crystal. International Journal of Unconventional Computing 3(4), 243-257 (2007
8. Harding, S.L., Miller, J.F., Rietman, E.A.: Evolution in materio: Exploiting the physics of materials for computation. International Journal of Unc onventional Computing 4(2), 155-194 (2008
9. Hollander, M., Wolfe, D.: Nonparametric statistical methods. Wiley (1973
10. Lykkebø , O.R., Harding, S., Tufte, G., Miller, J.F.: Mecobo: A hardware and software platform for in materio evolution. In: O.H. Ibarra, L. Kari, S. Kopecki (eds.) Unconventional Computation and Natural Computation, LNCS, pp. 267-279. Springer International Publishing (2014
11. Miller, J.F. (ed.): Cartesian Genetic Programming. Springer (2011
12. Miller, J.F., Downing, K.: Evolution in materio: Looking beyond the silicon box. In: NASA/DOD Conference on Evolvable Hardware, pp. 167-176. IEEE Comp. Soc. Press (2002
13. Miller, J.F., Harding, S.L., Tufte, G.: Evolution-in-materio: evolving computation in materials. Evolutionary Intelligence 7, 49- 67 (2014
14. Miller, J.F., Mohid, M. : Function optimization using cartesian genetic programming. In: GECCO (Companion), pp. 147-148 (2013
15. Mohid, M., Miller, J.F., Harding, S.L., Tufte, G., Lykkebø, O.R., Massey, M.K., Petty, M.C.: Evolution-in-materio: Solving machine learning classification problems using materials. In: Parallel Problem Solving from Nature-PPSN XIII-13th International Conference, Proceedings, LNCS, vol. 8672, pp. 721-730. Sp ringer (2014
16. Thompson, A.: Hardware Evolution-Automatic Design of Electronic Circuits in Reconfigurable Hardware by Artificial Evolution. Springer (1998
17. Thompson, A., Layzell, P.: Analysis of unconventional evolved electronics. Communications of the ACM 42(4), 71-79 (1999)
18. Vargha A.,Delaney H.D.: A critique and improvement of the cl common language effect size statistics of mcgraw and wong. Journal of Educational and Behavioral Statistics 25(2 101-132 2000)
19. Vesterstrom, J., Thomsen, R.: A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems. In: Evolutionary Computation, 2004. CEC2004. Congress on, vol. 2, pp. 1980-1987 (2004
20. Yao, X., Liu, Y.: Fast evolutionary programming. In: In L. J. Fogel et al. (Eds.), Proceedings of the 5th Annual Conference on Evolutionary Programming, pp. 451-460. MIT Press (1996)