Task Decomposition and Evolvability in Intrinsic Evolvable Hardware

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Kuyucu:2009:cec,

• author = "Tuze Kuyucu and Martin A. Trefzer and Julian F. Miller and Andy M. Tyrrell",
• title = "Task Decomposition and Evolvability in Intrinsic Evolvable Hardware",
• booktitle = "2009 IEEE Congress on Evolutionary Computation",
• year = "2009",
• editor = "Andy Tyrrell",
• pages = "2281--2287",
• address = "Trondheim, Norway",
• month = "18-21 " # may,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-2959-2",
• file = "P631.pdf",
• DOI = "doi:10.1109/CEC.2009.4983224",
• abstract = "Many researchers have encountered the problem that the evolution of electronic circuits becomes exponentially more difficult when problems with an increasing number of outputs are tackled. Although this is an issue in both intrinsic and extrinsic evolution experiments, overcoming this problem is particularly challenging in the case of evolvable hardware, where logic and routing resources are constrained according to the given architecture. Consequently, the success of experiments also depends on how the inputs and outputs are interfaced to the evolvable hardware. Various approaches have been made to solve the multiple output problem: partitioning the task with respect to the input or output space, incremental evolution of sub-tasks or resource allocation. However, in most cases, the proposed methods can only be applied in the case of extrinsic evolution. In this paper, we have accordingly, focused on scaling problem of increasing numbers of outputs when logic circuits are intrinsically evolved. We raise a number of questions: how big is the performance drop when increasing the number of outputs? Can the resources of evolvable hardware be structured in a suitable way to overcome the complexity imposed by multiple outputs, without including knowledge about the problem domain? Can available resources in hardware still be efficiently used when pre-structured? In order to answer these questions, different structural implementations are investigated. We have looked at these issues in solving three problems: 4-bit parity, 2-bit adder and 2-bit multiplier.",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• notes = "CEC 2009 - A joint meeting of the IEEE, the EPS and the IET. IEEE Catalog Number: CFP09ICE-CDR",

}

Genetic Programming entries for Tuze Kuyucu Martin A Trefzer Julian F Miller Andrew M Tyrrell

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