Sipper, M., Sanchez, E., Mange, D., Tomassini, M., Perez-Uribe, A., and Stau#er, A. A Phyl ogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems. IEEE Transactions on Evol utionary Computation, 1:1 (1997) 83--97.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....evolution [3, 5] After some successful applications of evolutionary algorithms to physical design (partitioning, placement and routing) now the same techniques are being considered also for structural design. This has given rise to an innovative field of research, called evolvable hardware [8, 19, 17]. Recently, evolutionary design automation has been applied to digital electronic design [14] It has been proposed for analog circuits as well, with encouraging results [12] The main concepts and issues relevant to evolutionary algorithms can be found, among others, in [16, 7, 4, 13, 11, 1] ....

M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. P'erez-Uribe, A. Stauffer. A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems, IEEE Trans. Evolutionary Computation, vol. 1, 1997.

....the mind. From a biological point of view, it has been determined that the genome contains the formation rules that specify the outline of the nervous system. Nevertheless, there is growing evidence that nervous systems follow an environmentally guided neural circuit building (neural epigenesis) (Sipper et al. 1997) that increases their learning flexibility and eliminates the heavy burden that nativism places on genetic mechanisms (Quartz and Sejnowski, 1997) The seminal work of the Nobel laureates D.H. Hubel and T.N. Wiesel on the brain s mechanism of vision (Hubel and Wiesel, 1979) describes a prime ....

M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. Perez-Uribe, and A. Stauffer. A Phylogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems. IEEE Transactions on Evolutionary Computation, 1(1):83--97, 1997.

....by GA. The individual represents the architecture bits. Then, GA is performed. The implementations of EHW from different reserch groups [2, 4, 5, 6] are various. But the similarity of various EHW are reconfigurable hardware, evolution and adaptation. The recent classification of EHW is defined in [7]. 1.4 Previous Work This paper is the extension of our previous work [8] which attempts to synthesize sequential circuit of which the behavior description is in the form of partial input output sequence. There are two related works, 9] and [10] Fogel evolved the state machine that can predict ....

M. Sipper, E. Shanchez, D. Mange, M. Tomassini, A. Perez-Uribe, and A. Stauffer. A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems. In IEEE Transactions on Evolutionary Computation, volume 1 No. 2, pages 83--97, 1997.

....circuit as chromosome in an evolutionary process in which the standard genetic operators such as initialisation, recombination, selection are carried out. The circuits may be evaluated using software simulation models [1] 2] 3] 4] or alternatively evolved entirely in hardware [5] 6 , 7] [8]. In this paper, we limit our focus to combinational logic circuits, which contain no memory elements. Such circuits contain no feedback paths. Note that this approach can be easily extended for the combinational multiple valued logic circuits. The approach is an extension of evolvable hardware ....

Sipper M., Sanchez E., Mange D., Tomassini M., Perez-Uribe A., and Stauffer A. (1997). A Phylogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems, in IEEE Trans. on Evolutionary Computation, Vol. 1, No 1., pp. 83-97.

....Law of Evolution. Biological systems develop and change during generations by combination and mutation of genes in chromosomes. In this way, new behavior arises and the most competitive individuals in the given environment survive and develop further. Another expression for this law is phylogeny [9]. 2. The Law of Learning. All individuals undergo learning through its lifetime. In this way, it learns to better survive in its environment. This law is also referred to as epigenesis [9] The two laws are concerning di#erent aspects of life and should be distinguished, when studying artificial ....

....in the given environment survive and develop further. Another expression for this law is phylogeny [9] 2. The Law of Learning. All individuals undergo learning through its lifetime. In this way, it learns to better survive in its environment. This law is also referred to as epigenesis [9]. The two laws are concerning di#erent aspects of life and should be distinguished, when studying artificial evolution. Most work on genetic algorithms are inspired by the Law of Evolution, while artificial neural networks are considering learning. Biological memory is still not fully understood. ....

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M. Sipper et al. A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems. IEEE Trans. on Evolutionary Computation, 1(1):83--97, April 1997.

....are related to the feasibility of evolving digital circuits. 1 Introduction Evolving a fully functional two bit multiplier in a configuration of logic cells is a simple case of digital circuit evolution, recently studied in the nascent field of evolvable hardware (Miller et al. 1997; Sipper et al. 1997; Thompson, 1998) Digital circuits have been evolved by Miller et al. 1997, 1998b, 1998a) who suggested that the design of electronic circuits on a gate array in general can be implemented in terms of the functionality and routing of the array. These refer to the logic functions utilised in the ....

Sipper, M., Sanchez, E., Mange, D., Tomassini, M., Perez-Uribe, A. and Stauffer, A. (1997). A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems. IEEE Transactions on Evolutionary Computation 1 (1), 83--97.

....with differing levels of connectivity, and show that the amount of routing and functional resource have a marked effect on the success of the evolutionary process. 0. Introduction There is, at the current time, a growing interest in designing electronic circuits using evolutionary techniques [11]. Koza [8] showed how simple digital circuits could be evolved using Genetic Programming, and Iba et al. 5] showed how it was possible to design circuits by evolving the functionality and connectivity of interconnected AND, OR, and NOT gates for intended use on a programmable logic array device ....

Sipper M., Sanchez E., Mange D., Tomassini M., Perez-Uribe A., and Stauffer A.: A Phylogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems, IEEE Transactions on Evolutionary Computation, Vol. 1, No 1., pp. 83-97.

....occurs in such a copying process, it can be regarded as evolution. It would be worth doing here to clarify the difference between self reproduction and self replication, since these terms have often been used in a confusing way. The difference between them has been discussed by Sipper et al.[52] According to their discussion, replication should be regarded as an ontogenetic, developmental process which involves no operation on genomes and results in an exact copying of the parent organism. On the other hand, reproduction should be regarded as a phylogenetic, evolutionary process which ....

Sipper, M., Sanchez, E., Mange, D., Tomassini, M., Prez-Uribe, A., and Stauffer, A. : A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems, IEEE Transactions on Evolutionary Computation, 1 No. 1, pp. 83--97 (1997).

....with repeating structures such as symmetry, segmentation, and subroutines. Adaptation. It is possible to grow phenotypes from genotypes adaptively, allowing constraints to be satisfied (Yu Bentley, 1998) improvement to variable conditions, and correction of malfunctions in designs (Sipper, 1997). Embryogenies also suffer from some drawbacks (Bentley, 1999) Can be hard to design. All types of embryogeny require careful design, and to date, only those researchers capable of performing this difficult art have demonstrated successful results. Can be hard to evolve. If care is not ....

Sipper, M. (1997) A Phylogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems.

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Sipper, M., Sanchez, E., Mange, D., Tomassini, M., Perez-Uribe, A., and Stau#er, A. A Phyl ogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems. IEEE Transactions on Evol utionary Computation, 1:1 (1997) 83--97.

....that enable the construction of artificial systems that live, grow, adapt, and reproduce in hardware would allow a quantum leap in performance for many computing systems known so far. If one considers life on Earth since its very beginning, three levels of organization can be distinguished [9, 13, 14]: Phylogeny: The first level concerns the temporal evolution of the genetic program, the hallmark of which is the evolution of species, or phylogeny. The multiplication of living organisms is based upon the reproduction of the program, subject to an extremely low error rate at the individual ....

M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. Perez-Uribe, and A. Stau#er. A Phylogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems. IEEE Transactions on Evolutionary Computation, 1(1):83--97, April 1997.

....its own sensors and effectors [14] Similar to the development of human infants, robots might interact with humans and their environment for extended periods of time, and become smarter autonomously, under human (adult) supervision. This may be achieved by endowing the robots with epigenetic [9] mechanisms (i.e. a chain of developmental processes activated after the initial action of the genes the description of the developmental program ) like adaptive categorization, trialand error learning, the construction of internal models, and imitation learning (See [5] and [7] A ....

M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. P'erez-Uribe, and A. Stauffer. A Phylogenetic, Ontogenetic, and Epigenetic View of Bio-Inspired Hardware Systems. IEEE Transactions on Evolutionary Computation, 1(1):83--97, April 1997.

....novel approaches and solutions to their problems. Basically, they have tried to understand and conceptualize the desired overall features or behaviors present in living organisms. Characteristics, such as evolution, fault tolerance, and adaptation have always been very interesting to engineers (Sipper et al. 1997). Social insect societies of ants, termites, wasps, and bees have interested researchers for their emergent complex behavior at the colonylevel (Bonabeau et al. 1997) Such behavior is the result of the interaction of many individuals doted with simple behaviors and simple learning capabilities. ....

Sipper, M., Sanchez, E., Mange, D., Tomassini, M., P'erez-Uribe, A., and Stauffer, A. (1997). A Phylogenetic, Ontogenetic, and Epigenetic View of BioInspired Hardware Systems. IEEE Transactions on Evolutionary Computation, 1(1):83--97.

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M. Sipper, E. Sanchez, D. Mange, M. Tomassini, A. Perez-Uribe, and A. Stau#er. A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems. IEEE Transactions on Evolutionary Computation, 1(1):83-- 97, April 1997.

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A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems. IEEE Transactions on Evolutionary Computation, vol. 1, no. 1. Steels, L. 1994. The artificial life roots of artificial intelligence. Artificial Life Journal, vol. 1, no. 1/2, pp 75--110. The MIT Press, Cambridge, MA.

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