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An Indexed Bibliography of Genetic Algorithms in Power Engineering
, 1995
"... s: Jan. 1992  Dec. 1994 ffl CTI: Current Technology Index Jan./Feb. 1993  Jan./Feb. 1994 ffl DAI: Dissertation Abstracts International: Vol. 53 No. 1  Vol. 55 No. 4 (1994) ffl EEA: Electrical & Electronics Abstracts: Jan. 1991  Dec. 1994 ffl P: Index to Scientific & Technical Proceedings: Ja ..."
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Cited by 73 (8 self)
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s: Jan. 1992  Dec. 1994 ffl CTI: Current Technology Index Jan./Feb. 1993  Jan./Feb. 1994 ffl DAI: Dissertation Abstracts International: Vol. 53 No. 1  Vol. 55 No. 4 (1994) ffl EEA: Electrical & Electronics Abstracts: Jan. 1991  Dec. 1994 ffl P: Index to Scientific & Technical Proceedings: Jan. 1986  Feb. 1995 (except Nov. 1994) ffl EI A: The Engineering Index Annual: 1987  1992 ffl EI M: The Engineering Index Monthly: Jan. 1993  Dec. 1994 The following GA researchers have already kindly supplied their complete autobibliographies and/or proofread references to their papers: Dan Adler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Ralf Bruns, I. L. Bukatova, Thomas Back, Yuval Davidor, Dipankar Dasgupta, Marco Dorigo, Bogdan Filipic, Terence C. Fogarty, David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina GorgesSchleuter, Jeffrey Horn, Aristides T. Hatjimihail, Mark J. Jakiela, Richard S. Judson, Akihiko Konaga...
Designing Electronic Circuits Using Evolutionary Algorithms. Arithmetic Circuits: A Case Study
, 1997
"... this article would inevitably be carrying out some kind of local search, given that it has been the authors' finding that the use of a low population size and very high number of generations gives better results. To explore this contention, consider the effect on the functionality of a chromosome wh ..."
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Cited by 66 (20 self)
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this article would inevitably be carrying out some kind of local search, given that it has been the authors' finding that the use of a low population size and very high number of generations gives better results. To explore this contention, consider the effect on the functionality of a chromosome when a single gene in a netlist chromosome is altered at random. The consequences in loss of functionality may be catastrophic as for instance, a primary output might, as a result, be connected to the wrong cell output. This observation implies that at the very least the local fitness landscape of a particular chromosome is very noisy. Another important factor here is the fact that the number of possible neighbours to a chromosome (defining a neighbour to be a chromosome which differs from the original in a single gene) is very large indeed. These two factors make it all the more surprising that low population sizes and high numbers of generations are more effective. One's sense of mystification is heightened when one recalls that elitism also improved the results. In an attempt to gain some insight into what is going on it is interesting to examine the history of gene changes of the best in the population as it develops from initially containing a large number of random elements to the final highly evolved form associated with possessing 100% functionality. Table 6.5 below shows the evolution of the best chromosome of the population. Each new improvement in fitness and the generation at which it occurred are also shown. In addition the fitness changes are shown and the number of different genes between chromosomes, where only genes which contributed to the functionality of the resulting circuit were counted (see also Figure 6.17). The chromosomes relate to a 3 x 4 geometry of ...
Evolving Digital Electronic Circuits for RealValued Function Generation using a Genetic Algorithm
 University of Wisconsin
, 1998
"... In this paper we describe experiments which attempt to evolve digital electronic circuits whose purpose is to implement real signals. As a convenience we chose to evolve mathematical functions i.e. the squareroot and sine. Real numbers in the range 0.000.99 are encoded in binary using four bits pe ..."
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Cited by 9 (7 self)
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In this paper we describe experiments which attempt to evolve digital electronic circuits whose purpose is to implement real signals. As a convenience we chose to evolve mathematical functions i.e. the squareroot and sine. Real numbers in the range 0.000.99 are encoded in binary using four bits per decimal place. The chromosome used is exactly modelled on the resources available on the Xilinx 6216 reconfigurable Field Programmable Gate Array (FPGA), so that evolved circuit designs may be simply implemented on this target device. We investigated a number of ways of presenting examples to the circuit so that the target function might be learned, and also looked at two distinctly different fitness function definitions. 1. Introduction There is, at the current time, a growing interest in the possibilities of designing electronic circuits using evolutionary techniques. A number of different approaches have been developed. Koza (Koza, 1992) showed how simple digital circuits could be evo...
Discovering Novel Digital Circuits using Evolutionary Techniques
 In IEE Colloquium on Evolvable Systems, IEE
, 1998
"... Modern FPGAs provide a platform for implementation of uncommitted logic arrays which are also, in many cases, reconfigurable. Whilst this allows circuit functionality to be changed in time, it also provides a convenient environment in which to encourage the direct evolution (using genetic algorithms ..."
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Cited by 5 (0 self)
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Modern FPGAs provide a platform for implementation of uncommitted logic arrays which are also, in many cases, reconfigurable. Whilst this allows circuit functionality to be changed in time, it also provides a convenient environment in which to encourage the direct evolution (using genetic algorithms) of those circuit solutions themselves. In this paper we describe experiments which examine the possibility of evolving simple arithmetic and mathematical circuits. We show that it is possible to evolve both conventional cellular designs  such as ripplecarry adders  and also very novel solutions which are suitable for implementation on arrays such as Xilinx 6000 series FPGAs. We also discuss the evolutionary models that are used to achieve this: evolving network connection lists, and then refining to produce a closer simulation of the actual internal structure of the Xilinx architecture. We then go on to examine and discuss the possibility of evolving mathematical functions  such as the...
Aspects of Digital Evolution: Geometry
 Proceedings of the Second International Conference on Evolvable Systems: From Biology to Hardware, Lecture Notes in Computer Science
, 1998
"... In this paper we present a new chromosome representation for evolving digital circuits. The representation is based very closely on the chip architecture of the Xilinx 6216 FPGA. We examine the effectiveness of evolving circuit functionality by using randomly chosen examples taken from the truth ..."
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In this paper we present a new chromosome representation for evolving digital circuits. The representation is based very closely on the chip architecture of the Xilinx 6216 FPGA. We examine the effectiveness of evolving circuit functionality by using randomly chosen examples taken from the truth table. We consider the merits of a cell architecture in which functional cells alternate with routing cells and compare this with an architecture in which any cell can implement a function or be merely used for routing signals. It is noteworthy that the presence of elitism significantly improves the Genetic Algorithm performance.