Development of Block-Stacking Teleo-Reactive Programs using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{srinivasan:2002:DBTPGP,
  author =       "Praveen Srinivasan",
  title =        "Development of Block-Stacking Teleo-Reactive Programs
                 using Genetic Programming",
  booktitle =    "Genetic Algorithms and Genetic Programming at Stanford
                 2002",
  year =         "2002",
  editor =       "John R. Koza",
  pages =        "233--242",
  address =      "Stanford, California, 94305-3079 USA",
  month =        jun,
  publisher =    "Stanford Bookstore",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.genetic-programming.org/sp2002/Srinivasan.pdf",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.7483",
  language =     "en",
  oai =          "oai:CiteSeerXPSU:10.1.1.140.7483",
  abstract =     "This paper describes the development of Teleo-Reactive
                 (T-R) block-stacking programs using genetic
                 programming. T-R programs are a class of programs that
                 are also a specific form of k-decision lists, and are
                 useful for programming tasks for autonomous agents.
                 Using only the predicates of On, a test to see if one
                 block is atop another, and Move, moving one block to
                 another{'}s column, genetic programming was able to
                 evolve programs capable of stacking 4 blocks in a
                 predefined order for as many as 500 different randomly
                 generated fitness cases. Programs for 5 and 6 block
                 situations were also successfully developed, but
                 attempts to create programs satisfying the desirable
                 regression property were largely unsuccessful.
                 Rewarding programs based on performing the least number
                 of moves after perfectly stacking blocks in all fitness
                 cases also had limited success, yielding an individual
                 likely generated by random chance and not by
                 evolution.",
  notes =        "part of \cite{koza:2002:gagp}",
}

Genetic Programming entries for Praveen Srinivasan

Citations