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Challenges of evolvable hardware: past, present and the path to a promising future

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Abstract

Nature is phenomenal. The achievements in, for example, evolution are everywhere to be seen: complexity, resilience, inventive solutions and beauty. Evolvable Hardware (EH) is a field of evolutionary computation (EC) that focuses on the embodiment of evolution in a physical media. If EH could achieve even a small step in natural evolution’s achievements, it would be a significant step for hardware designers. Before the field of EH began, EC had already shown artificial evolution to be a highly competitive problem solver. EH thus started off as a new and exciting field with much promise. It seemed only a matter of time before researchers would find ways to convert such techniques into hardware problem solvers and further refine the techniques to achieve systems that were competitive with or better than human designs. However, 15 years on—it appears that problems solved by EH are only of the size and complexity of that achievable in EC 15 years ago and seldom compete with traditional designs. A critical review of the field is presented. Whilst highlighting some of the successes, it also considers why the field is far from reaching these goals. The paper further redefines the field and speculates where the field should go in the next 10 years.

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Notes

  1. “Creating” refers to the creation of a physical entity.

References

  1. X. Yao, T. Higuchi, Promises and challenges of evolvable hardware. IEEE Trans. Syst. Man. Cybern. C 29(1), 87–97 (1999)

    Article  Google Scholar 

  2. T. Higuchi, M. Iwata, I. Kajitani, H. Iba, T. Furuya, B. Manderick, Evolvable hardware and its applications to pattern recognition and fault tolerant systems. Towards Evolvable Hardw. Evol. Eng. Approach, LNCS 1052, 118–135 (1996)

    Google Scholar 

  3. S.D. Scott, A. Samal, S. Seth, HGA: a hardware based genetic algorithm, in Proceedings of ACM/SIGDA 3rd International Symposium on FPGA’s, 1995, pp. 53–59

  4. M. Salami, G. Cain, Implementation of genetic algorithms on reprogrammable architectures, in Proceedings of the Eighth Australian Joint Conference on Artificial Intelligence (AI’95), 1995, pp. 121–128

  5. X. Yao, Evolutionary artificial neural networks. Int. J. Neural Syst. 4(3), 203–222 (1993)

    Article  Google Scholar 

  6. X. Yao, Y. Liu, Evolving artificial neural networks for medical applications, in Proceedings of 1995 Australia-Korea Joint Workshop on Evolutionary Computation, 1995, pp. 1–16

  7. X. Yao, Y. Liu, Towards designing artificial neural networks by evolution, in Proceedings of International Symposium on Artificial Life and Robotics (AROB), 1996, pp. 265–268, 18–20 Feb 1996

  8. X. Yao and Y. Liu, Evolving artificial neural networks through evolutionary programming, in The Fifth Annual Conference on Evolutionary Programming (MIT Press, 1996), pp. 257–266

  9. M.A. Rosenman, An evolutionary model for non-routine design, in Proceedings of the Eighth Australian Joint Conference on Artificial Intelligence (AI’95), (World Scientific Publ. Co., Singapore, 1995), pp. 363–370

  10. L. Davis, Handbook of Genetic Algorithms (Van Nostrand Reinhold, New York, NY, 1991)

    Google Scholar 

  11. T. Higuchi et al., Real-world applications of analog and digital evolvable hardware. IEEE Trans. Evol. Comput. 3(3), 220–235 (1999)

    Article  Google Scholar 

  12. A. Thompson, On the automatic design of robust electronics through artificial evolution, in Proceedings of the International Conference on Evolvable Systems: From Biology to Hardware, 1998, pp. 13–24

  13. J.A. Walker, J.A Hilder, A.M. Tyrrell, Evolving variability-tolerant CMOS designs, in Proceedings of the International Conference on Evolvable Systems: From Biology to Hardware, 2008, pp. 308–319

  14. S. Stepney, R.E. Smith, J. Timmis, A.M. Tyrrell, Towards a conceptual framework for artificial immune systems. Artif. Immune Syst., LNCS 3239(2004), 53–64 (2004)

    Article  Google Scholar 

  15. ispPAC30 Data Sheet (Lattice Semiconductor Corporation, 2001), http://www.latticesemi.com/lit/docs/datasheets/pac/pacover.pdf

  16. A. Stoica, D. Keymeulen, A. Thakoor, T. Daud, G. Klimech, Y. Jin, R. Tawel, V. Duong, Evolution of analog circuits on field programmable transistor arrays, in Proceedings of NASA/DoD Workshop on Evolvable Hardware (EH2000), 2000, pp. 99–108

  17. J. Langeheine, J. Becker, F. Folling, K. Meier, J. Schemmel, Initial studies of a new VLSI field programmable transistor array, in Proceedings 4th International Conference on Evolvable Systems: From Biology to Hardware, 2001, pp. 62–73

  18. Virtex Field Programmable Gate Arrays Data Book Version 2.5, (Xilinx Inc., 2001). http://www.xilinx.com

  19. User Manual and Tutorials for the CELL MATRIX MOD 88. http://www.cellmatrix.com

  20. E. Sanchez, D. Mange, M. Sipper, M. Tomassini, A. Perez-Uribe, A. Stauffer, Phylogeny, ontogeny, and epigenesis: three sources of biological inspiration for softening hardware, in Evolvable Systems: From Biology to Hardware, ICES 96, 1996, pp. 35–54

  21. A.M. Tyrrell, E. Sanchez, D. Floreano, G. Tempesti, D. Mange, J.M. Moreno, J. Rosenberg, A.E.P. Villa, POEtic tissue: an integrated architecture for bio-inspired hardware, in Proceedings of 5th International Conference on Evolvable Systems, (Trondheim, 2003), pp. 129–140

  22. A.J. Greensted, A.M. Tyrrell, Extrinsic evolvable hardware on the RISA architecture’, in 7th International Conference on Evolvable Systems, (Wuhan, China, 2007), pp. 244–255, September 2007

  23. J. Koza, Genetic Programming II: Automatic Discovery of Reusable Programs (MIT Press, Cambridge, MA, 1994)

    MATH  Google Scholar 

  24. J. Koza, M. Keane, M. Streeter, What’s AI done for me lately? Genetic programming’s human-competitive results. IEEE Intell. Syst. 18(3), 25–31 (2003)

    Article  Google Scholar 

  25. J. Koza, J. Yu, M.A. Keane, W. Mydlowec, Use of conditional developmental operators and free variables in automatically synthesizing generalized circuits using genetic programming, in Proceedings of the Second NASA/DoD Workshop on Evolvable Hardware, 2000, pp. 5–15

  26. M. Keane, J. Koza and M. Streeter, Automatic synthesis using genetic programming of an improved general-purpose controller for industrially representative plants, in Proceedings of the 2002NASA/DOD Conference On Evolvable Hardware, ed by A. Stoica, 2002, pp. 113–122

  27. M. Streeter, M. Keane, J. Koza, Routine duplication of post-2000 patented inventions by means of genetic programming, in Genetic Programming: 5th European Conference, EuroGP 2002, ed by J. Foster et al. (eds), 2002, pp. 26–36

  28. J. Koza, L.W. Jones, M.A. Keane, M.J. Streeter, S.H. Al-Sakran, Toward automated design of industrial-strength analog circuits by means of genetic programming, in Genetic Programming Theory and Practice II, Chap. 8, 2004, pp. 121–142

  29. E. Takahashi, Y. Kasai, M. Murakawa, T. Higuchi, Post fabrication clock-timing adjustment using genetic algorithms, in Evolvable Hardware, (Springer, 2006), pp. 65–84

  30. M. Murakawa, S. Yoshizawa, I. Kajitani, T. Furuya, M. Iwata, T. Higuchi, Hardware evolution at function level, in International Conference on Parallel Problem Solving in Nature, PPSN 1996, 1996, pp. 62–71

  31. I. Kajitani, T. Hoshino, N. Kajihara, M. Iwata, T. Higuchi, An evolvable hardware chip and its application as a multi-function prosthetic hand controller, in Proceedings of 16th National Conference on Artificial Intelligence (AAAI-99), 1999, pp. 182–187

  32. A. Stoica, T. Arslan, D. Keymeulen, V. Duong, X. Gou, R. Zebulum, I. Ferguson, T. Daud, Evolutionary recovery of electronic circuits from radiation induced faults, in IEEE Congress on Evolutionary Computation, IEEE CEC, 2004, pp. 1786–1793

  33. D. Linden, Optimizing signal strength in situ using an evolvable antenna system, n Proceedings of the 2002 NASA/DOD Conference On Evolvable Hardware, 2002, pp. 147–151

  34. J.D. Lohn, G. Hornby, A. Rodriguez-Arroyo, D. Linden, W. Kraus, S. Seufert, Evolutionary design of an x-band antenna for NASA’s space technology 5 mission, in 3rd NASA/DoD Conference on Evolvable Hardware, 2003, pp. 1–9

  35. M.L. Minsky, S.A. Papert, Perceptrons (MIT Press, Cambridge, MA, 1969)

    MATH  Google Scholar 

  36. S. Grossberg, Contour enhancement, short-term memory, and constancies in reverberating neural networks. Stud. Appl. Math. 52, 213–257 (1973)

    MATH  MathSciNet  Google Scholar 

  37. E. Bryson, Y.-C. Ho, Applied Optimal Control: Optimization, Estimation, and Control. (Blaisdell Publishing Company, New York, 1969)

  38. D.E. Rumelhart, G.E. Hinton, R.J. Williams, Learning representations by back-propagating errors, Letters to nature. Nature 323, 533–536 (1986)

    Article  Google Scholar 

  39. M. Hartmann, P.K. Lehre, P.C. Haddow, Evolved digital circuits and genome complexity, in NASA International Conference on Evolvable Hardware 2005, 2005, pp. 79–86

  40. J. Ziv, A. Lempel, A universal algorithm for sequential data compression. IEEE Trans. Inform. Theory IT-23(3), 337–343 (1977)

    Article  MathSciNet  Google Scholar 

  41. K. Kobayashi, J.M. Moreno, J. Madrenas, Implementation of a power-aware dynamic fault tolerant mechanism on the Ubichip platform, in International Conference on Evolvable Systems: From Biology to Hardware (ICES10), 2010, pp. 299–399

  42. International Technology RoadMap for Semiconductors (2009)

  43. A. Thompson, Evolutionary techniques for fault tolerance, in International Conference on Control, 1996, pp. 693–698

  44. P.C. Haddow, M. Hartmann, A. Djupdal, Addressing the metric challenge: evolved versus traditional fault tolerant circuits, in the 2nd NASA/ESA Conference on Adaptive Hardware and Systems, 2007, pp. 431–438

  45. T. Yu, S. Lee, Evolving cellular automata to model fluid flow in porous media, in 2002 NASA/DoD Conference on Evolvable Hardware, 2002, pp. 210–217

  46. R.S. Zebulum et al., Experimental results in evolutionary fault recovery for field programmable analogue devices, in Proceedings of the NASA/DOD International Conference on Evolvable Hardware, 2003, pp. 182–186

  47. A. Stoica et al., Temperature-adaptive ciruits on reconfigurable analog arrays, in IEEE Aerospace Conference 2007, 2007, pp. 1–6

  48. T. Kalganova, An extrinsic function-level evolvable hardware approach. Genetic Programming, Lecture Notes in Computer Science, vol. 1802, pp. 60–75 (2004)

  49. J. Torresen, A scalable approach to evolvable hardware, in The International Conference on Evolvable Systems: From Biology to Hardware, (ICES98), 1998, pp. 57–65

  50. J. Torresen, Scalable evolvable hardware applied to road image recognition, in The second NASA International Conference on Evolvable Hardware, 2000, pp. 245–252

  51. T. Kalganova, Bidirectional incremental evolution in extrinsic evolvable hardware, The second NASA/DoD Workshop on Evolvable Hardware, 2000, pp. 65–74

  52. W. Liu, M. Murakawa, T. Higuchi, ATM cell scheduling by functional level evolvable hardware, in Proceedings of the First International Conference on Evolvable Systems, 1996, pp. 180–192

  53. V.K. Vassilev, Scalability problems of digital circuit evolution: evolvability and efficient design, in Proceedings of the 2nd NASA/DoD Workshop on evolvable Hardware, 2000, pp. 55–64

  54. F. Gomaz, R. Miikulainen, Incremental evolution of complex general behaviour, in Special issue on Environment Structure and Behaviour, Adaptive Behaviour , vol 5, Issue 3–4. (MIT Press, 1997), pp. 317–342

  55. R.A. Brooks et al. Alternative essences of intelligence, in Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98) (AAAI Press, 1998), pp. 961–967

  56. J. H. Hong, S.B. Cho, MEH: modular evolvable hardware for designing complex circuits, in IEEE Congress on Evoutionary Computation, 2003, pp. 92–99

  57. E. Stomeo, T. Kalganova, C. Lambert, Generalized decomposition for evolvable hardware. IEEE Trans. Syst. Man Cybern. B 36(5), 1024–1043 (2006)

    Article  Google Scholar 

  58. E. Stomeo, T. Kalganova, Improving EHW performance introducing a new decomposition strategy. 2004 IEEE Conference on Cybernetics and Intelligent Systems, 2004, pp. 439–444

  59. T. Gordon, P.J. Bentley, Towards development in evolvable hardware, in Proceedings of the NASA/DoD Conference on Evolvable Hardware, 2002, pp. 241–250

  60. P.J. Bentley, Exploring component-based representations ? the secret of creativity by evolution, in Fourth International Conference on Adaptive Computing in Design and Manufacture, 2000, pp. 161–172

  61. F. Gruau, Neural network synthesis using cellular encoding and the genetic algorithm, PhD thesis, France, 1994

  62. H. Kitano, Designing neural networks using genetic algorithm with graph generation system. Complex Syst. 4, 461–476 (1990)

    MATH  Google Scholar 

  63. P.J. Bentley, S. Kumar, Three ways to grow designs: a comparison of embryogenies for an evolutionary design problem. in Genetic and Evolutionary Computation Conference (GECCO 99), 1999, pp. 35–43

  64. H. Kitano, Building complex systems using development process: an engineering approach. in Evolvable Systems: From Biology to Hardware, ICES, Lecture Notes in Computer Science, (Springer, 1998), pp. 218–229

  65. A.A. Siddiqi, S. Lucas, A comparison of matrix rewriting versus direct encoding for evolving neural networks. in Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, 1998, pp. 392–397

  66. P. Eggenberger, Creation of neural networks based on development and evolutionary principles, in Proceedings of the International Conference on ANNs, 1997, pp. 337–342

  67. H. Hemmi, J. Mizoguchi, K. Shimohara, Development and evolution of hardware behaviours. Towards Evolvable Hardw. LNCS 1062–1996, 250–265 (1996)

    Google Scholar 

  68. C. Ortega, A.M. Tyrrell, A hardware implementation of an embyonic architecture using virtex FPGAs, in Evolvable Systems: From Biology to Hardware, ICES, Lecture Notes in Computer Science, 2000, pp. 155–164

  69. P.C. Haddow, G. Tufte, P. ven remortel, Shrinking the genotype: L-systems for EHW? International Conference on Evolvable Systems: From Biology to Hardware, 2001, pp. 128–139

  70. J. Koza, M.A. Keane, M.J. Streeter, The importance of reuse and development in evolvable hardware, in Proceedings of the 2003 NASA/DoD Conference on Evolvable Hardware, 2003, pp. 33–42

  71. J.F. Miller, P. Thomson, A developmental method for growing graphs and circuits, in Proceedings of the 5th International Conference on Evolvable Systems (ICES03), 2003, pp. 93–104

  72. G. Tufte, P.C. Haddow, Towards development on a silicon-based cellular computing machine. J. Natural Comput. 4(4), 387–416 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  73. H. Liu, J.F. Miller, A.M. Tyrrell, Intrinsic evolvable hardware implementation of a robust biological development model for digital systems, in Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware, 2005, pp. 87–92

  74. P. van Remortel, J. Ceuppens, A. Defaweux, T. Lenaerts, B. Manderick, Developmental effects on tunable fitness landscapes, in Proceedings of the 5th International Conference on Evolvable Systems, ICES2003, 2003, pp. 117–128

  75. D. Roggen, D. Federici, Multi-cellular development: is there scalability and robustness to gain? in Proceedings of Parallel Problem Solving from Nature 8, PPSN 2004, 2004, pp. 391–400

  76. P.K. Lehre, P.C. Haddow, Developmental mappings and phenotypic complexity, in Proceedings of the Congress on Evolutionary Computation (CEC2003), 2003, pp. 62–68

  77. G. Tufte, Phenotypic developmental and computation resources: scaling in artificial development, in Genetic and Evolutionary Computation Conference, 2008, pp. 859–866

  78. J.A. Walker, J.F. Miller, The automatic acquisiation, evolution and re-use of modules in Cartesian genetic programming. IEEE Trans. Evol Comput 12(4), 1–21 (2008)

    Article  Google Scholar 

  79. J.A. Walker, J.F. Miller, Evolution and acquisition of modules in Cartesian genetic programming, in Proceedings of the 7th European Conference Genetic Programming (EuroGP 2004), vol. 3003, Lecture Notes in Computer Science, 2004, pp. 187–197

  80. J.F. Miller, P. Thomson, Aspects of digital evolution: geometry and learning, in Proceedings of the International Conference on Evolvable Systems: From Biology to Hardware, 1998, pp. 25–35

  81. Z. Vazilicek et al., On evolutionary synthesis of linear transforms in FPGA, in International Conference on Evolvable Systems: From Biology to Hardware 2008, LNCS, 5216, 141–152 (2008)

  82. A. Thompson, An evolved circuit, intrinsic in silicon, entwined with physics, 1st International Conference on Evolvable Systems 1996 (Springer, 1996), pp. 390–405

  83. J. Lohn, G. Hornby, Evolvable hardware using evolutionary computation to design and optimize hardware systems, IEEE Computational Intelligence Magazine, feb., 2006, pp. 19–27

  84. S.L. Harding, J.F. Miller, E.A. Rietman, Evolution in Materio: exploiting the physics of materials for computation. Int. J. Unconv. Comput. 4(2), 155–194 (2008)

    Google Scholar 

  85. S.L. Harding, J.F. Miller, Evolution in materio: a tone discriminator in liquid crystal, Congress on Evolutionary Computation, 2004, pp. 1800–1807

  86. S.L. Harding, J.F. Miller, Evolution in materio: investigating the stability of robot controllers evolved in liquid crystal, The international Conference on Evolvable Systems: From Biology to Hardware, 2005, pp. 155–164

  87. S. H. Mahdavi, P. Bentley, Evolving motion of robots with muscles, in Applications of Evolutionary Computing, LNCS, 2611, 149–155 (2003)

  88. M. Oteam, Switchable glass: a possible medium for evolvable hardware, First NASA/ESA Conference on Adaptive Hardware and Systems, 2006, pp. 81–87

  89. A. Thompson, Hardware evolution: automatic design of electronic circuits in reconfigurable hardware by artificial evolution, Distinguished Dissertation Series, Springer, 1998

  90. M. Garvie, A. Thompson, Evolution of combinatonial and sequential on-line selfdiagnosing hardware, in Proceedings of the 5th NASA/DoD Workshop on Evolvable Hardware, 2003, pp. 177–183

  91. J.D. Lohn, G.V. Larchev, R.F. Demara, A genetic representation for evolutionary fault recovery in Virtex FPGAs, in Proceedings of the 5th International Conference on Evolvable Systems: From Biology to Hardware (ICES), 2003, pp. 47–56

  92. K. Zhang, R.F. Demara, C.A. Sharma, Consensus-based evaluation for fault isolation and on-line evolutionary regeneration, in Proceedings of the 6th International Conference on Evolvable Systems: From Biology to Hardware (ICES05), 2005, pp. 12–24

  93. F. Corno, G. Cumani, M.S. Reorda, G. Squillero, Efficient machine-code test-program induction. in Proceedings of the Congress on Evolutionary Computation (CEC), IEEE, 2002, pp. 1486–1491

  94. T. Pecenka, Z. Kotasek, L. Sekanina, J. Strnadel, Automatic discovery of RTL benchmark circuits with predefined testability properties, in Proceedings of the NASA/DoD Conference on Evolvable Hardware, 2005, pp. 51–58

  95. T. Pecanka, L. Sekanina, Z. Kotasek, Evolution on synthetic rtl benchmark circuits with predefined testability. ACM Trans. Design Autom. Electron. Syst. 13(3), 1–21 (2008)

    Article  Google Scholar 

  96. K. Kobayashi, J.M. Moreno, J. Madreas, Implementation of a power-aware dynamic fault tolerant mechanism on the Ubichip platform, International Conference on Evolvable Systems: From Biology to Hardware, 2010, pp. 299–309

  97. A. Djupdal, P.C. Haddow, Evolving efficient redundancy by exploiting the analogue nature of CMOS transistors, Fourth International Conference on Computational Intelligence, Robotics and Autonomous Systems (CIRAS), 2007, pp. 81–86

  98. D. Keymeulen, R.S. Zebulum, Y. Jin, A. Stoica, Fault-tolerant evolvable hardware using field-programmable transistor arrays. IEEE Trans. Reliab. 49(3), 305–316 (2000)

    Article  Google Scholar 

  99. G. Greenwood, A.M. Tyrrell, Metamorphic systems: a new model for adaptive systems design, in Proceedings of the Congress on Evolutionary Computation, 2010, pp. 3261–3268

  100. J.F. Miller, K. Downing, Evolution in materio: looking beyond the silicon box, NASA/DoD Conference on Evolvable Hardware (EH’02), 2002, pp. 167–178

  101. L. Sekanina, Evolvable hardware: from applications to implications for the theory of computation, Unconv. Comput. LNCS, 5715, 24–36 (2009)

    Google Scholar 

  102. S. Stepney, The neglected pillar of material computation. Physica D 237(9), 1157–1164 (2008)

    Article  MATH  MathSciNet  Google Scholar 

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  1. CRAB Lab, Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway

    Pauline C. Haddow

  2. Intelligent Systems Group, Department of Electronics, University of York, York, UK

    Andy M. Tyrrell

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Haddow, P.C., Tyrrell, A.M. Challenges of evolvable hardware: past, present and the path to a promising future. Genet Program Evolvable Mach 12, 183–215 (2011). https://doi.org/10.1007/s10710-011-9141-6

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