Field Report: Applying Monte Carlo Tree Search for Program Synthesis

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Jin-Suk Lim and Shin Yoo",
  title =        "Field Report: Applying {Monte Carlo Tree Search} for
                 Program Synthesis",
  booktitle =    "Proceedings of the 8th International Symposium on
                 Search Based Software Engineering, SSBSE 2016",
  year =         "2016",
  editor =       "Federica Sarro and Kalyanmoy Deb",
  volume =       "9962",
  series =       "LNCS",
  pages =        "304--310",
  address =      "Raleigh, North Carolina, USA",
  month =        "8-10 " # oct,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, MCTS",
  isbn13 =       "978-3-319-47106-8",
  URL =          "",
  DOI =          "doi:10.1007/978-3-319-47106-8_27",
  abstract =     "Program synthesis aims to automatically generate an
                 executable segment of code that satisfies a given set
                 of criteria. Genetic programming has been widely
                 studied for program synthesis. However, it has
                 drawbacks such as code bloats and the difficulty in
                 finer control over the growth of programs. This paper
                 explores the possibility of applying Monte Carlo Tree
                 Search (MCTS) technique to general purpose program
                 synthesis. The exploratory study applies MCTS to
                 synthesis of six small benchmarks using Java Bytecode
                 instructions, and compares the results to those of
                 genetic programming. The paper discusses the major
                 challenges and outlines the future work.",
  notes =        "cites \cite{Helmuth:2015:GECCO} Web page (Aug 2016)
                 says 'MCTS performs comparably to GP'.

                 co-located with ICSME-2016 gismo",

Genetic Programming entries for Jinsuk Lim Shin Yoo