Evolution in Materio: Exploiting the Physics of Materials for Computation

We describe several techniques for using bulk matter for special purpose computation. In each case it is necessary to use an evolutionary algorithm to program the substrate on which the computation is to take place. In addition, the computation comes about as a result of nearest neighbour interactions at the nano- micro- and meso-scale. In our first example we describe evolving a saw-tooth oscillator in a CMOS substrate. In the second example we demonstrate the evolution of a tone discriminator by exploiting the physics of liquid crystals. In the third example we outline using a simulated magnetic quantum dot array and an evolutionary algorithm to develop a pattern matching circuit. Another example we describe exploits the micro-scale physics of charge density waves in crystal lattices. We show that vastly different resistance values can be achieved and controlled in local regions to essentially construct a programmable array of coupled micro-scale quasiperiodic oscillators. Lastly we show an example where evolutionary algorithms could be used to control density modulations, and therefore refractive index modulations, in a fluid for optical computing

Neural Computation with Rings of Quasiperiodic Oscillators

We describe the use of quasiperiodic oscillators for computation and control of robots. We also describe their relationship to central pattern generators in simple organisms and develop a group theory for describing the dynamics of these systems.Comment: 54 pages, 26 figure

Evolvable hardware design of combinational logic circuits.

Evolvable Hardware (EHW), as an alternative method for logic design, became moreattractive recently, because of its algebra-independent techniques for generating selfadaptiveself-reconfigurable hardware. This thesis investigates and relates both evaluationand evolutionary processes, emphasizing the need to address problems arisingfrom data complexity.Evaluation processes, capable of evolving cost-optimised fully functional circuitsare investigated. The need for an extrinsic EHW approach (software models) independentof the concerns of any implementation technologies is emphasized. It is alsoshown how the function description may be adapted for use in the EHW approach.A number of issues of evaluation process are addressed: these include choice of optimisationcriteria, multi-objective optimisation tedmiques in EHW and probabilisticanalysis of evolutionary processes.The concept of self-adaptive extrinsic EHW method is developed. This approachemphasizes the circuit layout evolution together with circuit functionality. A chromosomerepresentation for such system is introduced, and a number of genetic operatorsand evolutionary algorithms in support of this approach are presented. The geneticoperators change the genetic material at the different levels of chromosome representation.Furthermore, a chromosome representation is adapted to the function-levelEHW approach. As a result, the modularised systems are evolved using multi-outputbuilding blocks. This chromosome representation overcomes the problem of longstring chromosome.Together, these techniques facilitate the construction of systems to evolve logicfunctions of large number of variables. A method for achieving this using bidirectionalincremental evolution is documented. It is demonstrated that the integration of adynamic evaluation process and self-adaptive function-level EHW approach allowsthe bidirectional incremental evolution to successfully evolve more complex systemsthan traditionally evolved before. Thereby it provides a firm foundation for theevolution of complex systems.Finally, the universality of these techniques is proved by applying them to multivaluedcombinational logic design. Empirical study of this application shows thatthere is no fundamental difference in approach for both binary and multi-valued logicdesign problems