An Investigation into the use of Evolutionary Algorithms for Fully Automated Planning

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

@PhdThesis{Westerberg:thesis,
  author =       "Carl Henrik Westerberg",
  title =        "An Investigation into the use of Evolutionary
                 Algorithms for Fully Automated Planning",
  school =       "Artificial Intelligence Applications Institute, School
                 of Informatics, University of Edinburgh",
  year =         "2006",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.cis.strath.ac.uk/~henrik/publications/thesis.pdf",
  size =         "329 pages",
  abstract =     "This thesis presents a new approach to the Artificial
                 Intelligence (AI) problem of fully automated planning.
                 Planning is the act of deliberation before acting that
                 guides rational behaviour and is a core area of AI.
                 Many practical real-world problems can be classed as
                 planning problems, therefore practical and theoretical
                 developments in AI planning are well motivated.
                 Unfortunately, planning for even toy domains is hard,
                 many different search algorithms have been proposed,
                 and new approaches are actively encouraged.

                 The approach taken in this thesis is to adopt ideas
                 from Evolutionary Algorithms (EAs) and apply the
                 techniques to fully automated plan synthesis. EA
                 methods have enjoyed great success in many problem
                 areas of AI. They are a new kind of search technique
                 that have their foundation in evolution. Previous
                 attempts to apply EAs to plan synthesis have promised
                 encouraging results, but have been ad-hoc and
                 piecemeal.

                 This thesis thoroughly investigates the approach of
                 applying evolutionary search to the fully automated
                 planning problem. This is achieved by developing and
                 modifying a proof of concept planner called GENPLAN.
                 Before EA-based systems can be used, a thorough
                 examination of various parameter settings must be
                 explored. Once this was completed, the performance of
                 GENPLAN was evaluated using a selection of benchmark
                 domains and other competition style planners. The
                 difficulties raised by the benchmark domains and the
                 extent to which they cause problems for the approach
                 are highlighted along with problems associated with EA
                 search. Modifications are proposed and experimented
                 with in an attempt to alleviate some of the identified
                 problems. EAs offer a flexible framework for fully
                 automated planning, but demonstrate a clear weakness
                 across a range of currently used benchmark domains for
                 plan synthesis.",
}

Genetic Programming entries for Carl Henrik Westerberg

Citations