Trustworthy Genetic Programming-Based Synthesis of Analog Circuit Topologies Using Hierarchical Domain-Specific Building Blocks

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Article{McConaghy:2012:ieeetec,
  author =       "Trent McConaghy and Pieter Palmers and 
                 Michiel Steyaert and Georges G. E. Gielen",
  title =        "Trustworthy Genetic Programming-Based Synthesis of
                 Analog Circuit Topologies Using Hierarchical
                 Domain-Specific Building Blocks",
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2011",
  volume =       "15",
  number =       "4",
  pages =        "557--570",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, Analog,
                 Analog circuits, Design automation, Grammar, Integrated
                 circuit modelling, Semiconductor process modeling,
                 Solid modeling, Topology, design automation,
                 evolutionary algorithm (EA), integrated circuit (IC),
                 multiobjective optimisation",
  ISSN =         "1089-778X",
  URL =          "http://trent.st/content/2011-TEVC-mojito-ea.pdf",
  DOI =          "doi:10.1109/TEVC.2010.2093581",
  size =         "14 pages",
  abstract =     "This paper presents MOJITO, a system that performs
                 structural synthesis of analog circuits, returning
                 designs that are trustworthy by construction. The
                 search space is defined by a set of expert-specified,
                 trusted, hierarchically-organised analog building
                 blocks, which are organized as a parametrised
                 context-free grammar. The search algorithm is a
                 multiobjective evolutionary algorithm that uses an
                 age-layered population structure to balance exploration
                 versus exploitation. It is validated with experiments
                 to search across more than 100000 different one-stage
                 and two-stage opamp topologies, returning
                 human-competitive results. The runtime is orders of
                 magnitude faster than open-ended systems, and unlike
                 the other evolutionary algorithm approaches, the
                 resulting circuits are trustworthy by construction. The
                 approach generalises to other problem domains which
                 have accumulated structural domain knowledge, such as
                 robotic structures, car assemblies, and modelling
                 biological systems.",
  notes =        "Also known as \cite{5699917}",
}

Genetic Programming entries for Trent McConaghy Pieter Palmers Michiel Steyaert Georges G E Gielen

Citations