Evolved Computing Devices and the Implementation Problem

The evolutionary circuit design is an approach allowing engineers to realize computational devices. The evolved computational devices represent a distinctive class of devices that exhibits a specific combination of properties, not visible and studied in the scope of all computational devices up till now. Devices that belong to this class show the required behavior; however, in general, we do not understand how and why they perform the required computation. The reason is that the evolution can utilize, in addition to the “understandable composition of elementary components”, material-dependent constructions and properties of environment (such as temperature, electromagnetic field etc.) and, furthermore, unknown physical behaviors to establish the required functionality. Therefore, nothing is known about the mapping between an abstract computational model and its physical implementation. The standard notion of computation and implementation developed in computer science as well as in cognitive science has become very problematic with the existence of evolved computational devices. According to the common understanding, the evolved devices cannot be classified as computing mechanisms.

[1]  Mark A. Ratner,et al.  Molecular electronics , 2005 .

[2]  Jan van Leeuwen,et al.  Relativistic Computers and Non-uniform Complexity Theory , 2002, UMC.

[3]  Jan van Leeuwen,et al.  The Turing machine paradigm in contemporary computing , 2001 .

[4]  Clive Richards,et al.  The Blind Watchmaker , 1987, Bristol Medico-Chirurgical Journal.

[5]  Vu Duong,et al.  Evolvable hardware techniques for on-chip automated reconfiguration of programmable devices , 2004, Soft Comput..

[6]  Peter Wegner,et al.  Turing’s Ideas and Models of Computation , 2004 .

[7]  Xiaofan Luo,et al.  Molecular Electronics , 2009 .

[8]  Paul J. Layzell,et al.  Explorations in design space: unconventional electronics design through artificial evolution , 1999, IEEE Trans. Evol. Comput..

[9]  Ricardo Salem Zebulum,et al.  Evolutionary Electronics , 2001 .

[10]  Tughrul Arslan,et al.  Evolvable Components—From Theory to Hardware Implementations , 2005, Genetic Programming and Evolvable Machines.

[11]  Colin G. Johnson What kinds of natural processes can be regarded as computations , 2004 .

[12]  Peter J. Bentley,et al.  Evolutionary Design By Computers , 1999 .

[13]  Hitoshi Iba,et al.  Evolving hardware with genetic learning: a first step towards building a Darwin machine , 1993 .

[14]  Julian Francis Miller,et al.  Evolution in materio: looking beyond the silicon box , 2002, Proceedings 2002 NASA/DoD Conference on Evolvable Hardware.

[15]  John R. Searle,et al.  Is the Brain a Digital Computer , 1990 .

[16]  Robin Gandy,et al.  Church's Thesis and Principles for Mechanisms , 1980 .

[17]  S. Lloyd Ultimate physical limits to computation , 1999, Nature.

[18]  Bruce J. MacLennan,et al.  Transcending Turing Computability , 2003, Minds and Machines.

[19]  Hugo de Garis,et al.  EVOLVABLE HARDWARE Genetic Programming of a Darwin Machine , 1993 .

[20]  Julian Francis Miller,et al.  Principles in the Evolutionary Design of Digital Circuits—Part II , 2000, Genetic Programming and Evolvable Machines.

[21]  Mike Stannett,et al.  Computation and Hypercomputation , 2003, Minds and Machines.

[22]  B. Jack Copeland Super turing-machines , 1998 .

[23]  Peter J. Bentley,et al.  Evolutionary Design by Computers with CDrom , 1999 .

[24]  Christoph H. Keitel,et al.  Relativistic and radiative corrections to the Mollow spectrum (20 pages) , 2004 .

[25]  Julian Francis Miller,et al.  Evolution In Materio: Evolving Logic Gates in Liquid Crystal , 2007, Int. J. Unconv. Comput..

[26]  Dr. Zbigniew Michalewicz,et al.  How to Solve It: Modern Heuristics , 2004 .

[27]  R. Brooks The relationship between matter and life , 2001, Nature.

[28]  Brian Cantwell Smith,et al.  The Foundations of Computing , 1996 .

[29]  Kenji Toda,et al.  Real-world applications of analog and digital evolvable hardware , 1999, IEEE Trans. Evol. Comput..

[30]  Adrian Thompson,et al.  Hardware evolution - automatic design of electronic circuits in reconfigurable hardware by artificial evolution , 1999, CPHC/BCS distinguished dissertations.

[31]  B. Copeland,et al.  Beyond the universal Turing machine , 1999 .

[32]  Lukáš Sekanina,et al.  Evolvable computing by means of evolvable components , 2004, Natural Computing.

[33]  Lukás Sekanina,et al.  Evolutionary discovering of the concept of the discrete state at the transistor level , 2005, 2005 NASA/DoD Conference on Evolvable Hardware (EH'05).

[34]  Vu Duong,et al.  Circuit self-recovery experiments in extreme environments , 2004, Proceedings. 2004 NASA/DoD Conference on Evolvable Hardware, 2004..

[35]  Peter Wegner,et al.  Computation beyond turing machines , 2003, CACM.

[36]  Ray Paton Computation in cells and tissues : perspectives and tools of thought , 2004 .

[37]  Randy A. Bartels,et al.  Learning from learning algorithms: Application to attosecond dynamics of high-harmonic generation , 2004 .

[38]  Gualtiero Piccinini,et al.  Computations and Computers in the Sciences of Mind and Brain , 2003 .

[39]  Matthias Scheutz,et al.  When Physical Systems Realize Functions... , 1999, Minds and Machines.

[40]  N. Blackstone Essential Cell Biology: An Introduction to the Molecular Biology of the Cell.Bruce Alberts , Dennis Bray , Alexander Johnson , Julian Lewis , Martin Raff , Keith Roberts , Peter Walter , 1998 .

[41]  Adrian Stoica,et al.  Fault-tolerant evolvable hardware using field-programmable transistor arrays , 2000, IEEE Trans. Reliab..

[42]  A. Turing On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .

[43]  B. Jack Copeland,et al.  Super Turing-machines , 1998, Complex..