This paper introduces a Minimum Description Length (MDL) principle to define fitness functions in Genetic Programming (GP). In traditional (Koza-style) GP, the size of trees was usually controlled by user-defined parameters, such as the maximum number of nodes and maximum tree depth. Large tree sizes meant that the time necessary to measure their fitnesses often dominated total processing time. To overcome this difficulty, we introduce a method for controlling tree growth, which uses an MDL principle. Initially we choose a "decision tree" representation for the GP chromosomes, and then show how an MDL principle can be used to define GP fitness functions. Thereafter we apply the MDL-based fitness functions to some practical problems. Using our implemented system "STROGANOFF", we show how MDL-based fitness functions can be applied successfully to problems of pattern recognitions. The results demonstrate that our approach is superior to usual neural networks in terms of general...

This paper describes an automated process for designing electrical circuits in which "What You Want Is What You Get " ("WYWIWYG " – pronounced "wow-eee-wig"). The design process uses genetic programming to produce both the topology of the desired circuit and the sizing (numerical values) for all the components of a circuit. Genetic programming successfully evolves both the topology and the sizing for an asymmetric bandpass filter that was described as being difficult-to-design in a leading electrical engineering journal. This evolved circuit is another instance in which a genetically evolved solution to a non-trivial problem is competitive with human performance. 1.

: This paper describes an automated process for designing analog electrical circuits based on the principles of natural selection, sexual recombination, and developmental biology. The design process starts with the random creation of a large population of program trees composed of circuit-constructing functions. Each program tree specifies the steps by which a fully developed circuit is to be progressively developed from a common embryonic circuit appropriate for the type of circuit that the user wishes to design. Each fully developed circuit is translated into a netlist, simulated using a modified version of SPICE, and evaluated as to how well it satisfies the user's design requirements. The fitness measure is a user-written computer program that may incorporate any calculable characteristic or combination of characteristics of the circuit, including the circuit's behavior in the time domain, its behavior in the frequency domain, its power consumption, the number of components, cost o...

Abstract – It would be desirable if computers could solve problems without the need for a human to write the detailed programmatic steps. That is, it would be desirable to have a domain-independent automatic programming technique in which "What You Want Is What You Get " ("WYWIWYG " – pronounced "woweee-wig"). Genetic programming is such a technique. This paper surveys three recent examples of problems (from the fields of cellular automata and molecular biology) in which genetic programming evolved a computer program that produced results that were slightly better than human performance for the same problem. This paper then discusses the problem of electronic circuit synthesis in greater detail. It shows how genetic programming can evolve both the topology of a desired electrical circuit and the sizing (numerical values) for each component in a crossover (woofer and tweeter) filter. Genetic programming has also evolved the design for a lowpass filter, the design of an amplifier, and the design for an asymmetric bandpass filter that was described as being difficult-to-design in an article in a leading electrical engineering journal.

Most practical electrical circuits contain modular substructures that are repeatedly used to create the overall circuit. Genetic programming with automatically defined functions and the recently developed architecturealtering operations provides a way to build complex structures with reused substructures. In this paper, we successfully evolved a design for a twoband crossover (woofer and tweeter) filter with a crossover frequency of 2,512 Hz. Both the topology and the sizing (numerical values) for each component of the circuit were evolved during the run. The evolved circuit contained three different noteworthy substructures. One substructure was invoked five times thereby illustrating reuse. A second substructure was invoked with different numerical arguments. This second substructure illustrates parameterized reuse because different numerical values were assigned to the components in the different instantiations of the substructure. A third substructure was invoked as part of a hierarchy, thereby illustrating hierarchical reuse.

The dominant component of the computational burden of solving nontrivial problems with evolutionary algorithms is the task of measuring the fitness of each individual in each generation of the evolving population. The advent of rapidly reconfigurable field-programmable gate arrays (FPGAs) and the idea of evolvable hardware opens the possiblity of embodying each individual of the evolving population into hardware for the purpose of accelerating the timeconsuming fitness evaluation task This

Genetic programming was used to evolve both the topology and the sizing (numerical values) for each component of a low-distortion, lowbias 60 decibel (1000-to-1) amplifier circuit with good frequency generalization. The evolved circuit was composed of two types of transistors (active elements) as well as resistors and capacitors. 1. Introduction The problem of circuit synthesis involves designing an electrical circuit that satisfies user-specified design goals. A complete design of an electrical circuit includes both its topology and the sizing of all its components. The topology of a circuit consists of the number of components in the circuit, the type of each component, and a list of all the connections between the components. The sizing of a circuit consists of the component value(s) of each component. Evolvable hardware is one approach to automated circuit synthesis. Some of the early pioneering work in this field includes that of Higuchi, Niwa, Tanaka, Iba, de Garis, and Furuya...

It would be desirable if computers could solve problems without the need for a human to write the detailed programmatic steps. That is, it would be desirable to have a domain-independent automatic programming technique in which "What You Want Is What You Get" ("WYWIWYG" -- pronounced "wow-eee-wig"). Genetic programming is such a technique. This paper surveys three recent examples of problems (one from the field of cellular automata and two from the fields of molecular biology) in which genetic programming evolved a computer program that produced results that were slightly better than human performance for the same problem. This paper then discusses a fourth problem in greater detail and demonstrates that a design for a low-distortion 96 decibel op amp (including both topology and component sizing) can be evolved using genetic programming. The information that the user must supply to genetic programming consists of the parts bin (transistors, resistors, and capacitors) and the fitness m...

Abstract: This paper describes an automated process for designing analog electrical circuits based on the principles of natural selection, sexual recombination, and developmental biology. The design process starts with the random creation of a large population of program trees composed of circuit-constructing functions. Each program tree specifies the steps by which a fully developed circuit is to be progressively developed from a common embryonic circuit appropriate for the type of circuit that the user wishes to design. Each fully developed circuit is translated into a netlist, simulated using a modified version of SPICE, and evaluated as to how well it satisfies the user's design requirements. The fitness measure is a user-written computer program that may incorporate any calculable characteristic or combination of characteristics of the circuit, including the circuit's behavior in the time domain, its behavior in the frequency domain, its power consumption, the number of components, cost of components, or surface area occupied by its components. The population of program trees is genetically bred over a series of many generations using genetic programming. Genetic programming is driven by a fitness measure and employs genetic operations such as Darwinian reproduction,