Adaptive problem solving method and apparatus utilizing evolutionary computation techniques

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Misc{gounares:2001:patent,
  author =       "Alexander Gounares and Prakash Sikchi",
  title =        "Adaptive problem solving method and apparatus
                 utilizing evolutionary computation techniques",
  howpublished = "U.S. Patent",
  year =         "2001",
  month =        "28 " # aug,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://patft.uspto.gov/netacgi/nph-Parser?Sect2=PTO1&Sect2=HITOFF&p=1&u=/netahtml/PTO/search-bool.html&r=1&f=G&l=50&d=PALL&RefSrch=yes&Query=PN/6282527",
  abstract =     "A system for adaptively solving sequential problems in
                 a target system using evolutionary computation
                 techniques and in particular genetic algorithms and
                 modified genetic algorithms. Stimuli to a target system
                 such as a software system are represented as actions. A
                 single sequence of actions is a chromosome. Chromosomes
                 are generated by a goal-seeking algorithm that uses a
                 hint database and recursion to intelligently and
                 efficiently generate a robust chromosome population.
                 The chromosomes are applied to the target system one
                 action at a time and the change in properties of the
                 target system is measured after each action is applied.
                 A fitness rating is calculated for each chromosome
                 based on the property changes produced in the target
                 system by the chromosome. The fitness rating
                 calculation is defined so that successive generations
                 of chromosomes will converge upon desired
                 characteristics. For example, desired characteristics
                 for a software testing application are defect discovery
                 and code coverage. Chromosomes with high fitness
                 ratings are selected as parent chromosomes and various
                 techniques are used to mate the parent chromosomes to
                 produce children chromosomes. Children chromosomes with
                 high fitness ratings are entered into the chromosome
                 population. Defects in a target software system are
                 minimised by evolving ever-shorter chromosomes that
                 produce the same defect. Defect discovery rate, or any
                 other desired characteristic, is thereby maximised.",
  notes =        "6,282,527 Assignee: Microsoft Corporation (Redmond,
                 WA)",
}

Genetic Programming entries for Alexander Gounares Prakash Sikchi

Citations