Real-Time GA-Based Probabilistic Programming in Application to Robot Control

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Alexey Potapov and Sergey Rodionov and Vita Potapova",
  title =        "Real-Time GA-Based Probabilistic Programming in
                 Application to Robot Control",
  booktitle =    "Artificial General Intelligence",
  year =         "2016",
  editor =       "Bas Steunebrink and Pei Wang and Ben Goertzel",
  volume =       "9782",
  series =       "LNCS",
  pages =        "95--105",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-41649-6",
  DOI =          "doi:10.1007/978-3-319-41649-6_10",
  abstract =     "Possibility to solve the problem of planning and plan
                 recovery for robots using probabilistic programming
                 with optimization queries, which is being developed as
                 a framework for AGI and cognitive architectures, is
                 considered. Planning can be done directly by
                 introducing a generative model for plans and optimizing
                 an objective function calculated via plan simulation.
                 Plan recovery is achieved almost without modifying
                 optimization queries. These queries are simply executed
                 in parallel with plan execution by a robot meaning that
                 they continuously optimize dynamically varying
                 objective functions tracking their optima. Experiments
                 with the NAO robot showed that replanning can be
                 naturally done within this approach without developing
                 special plan recovery methods.",

Genetic Programming entries for Alexey Potapov Sergey Rodionov Vita Potapova