Generating heuristics for novice players

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Fernando {de Mesentier Silva} and Aaron Isaksen and 
                 Julian Togelius and Andy Nealen",
  booktitle =    "2016 IEEE Conference on Computational Intelligence and
                 Games (CIG)",
  title =        "Generating heuristics for novice players",
  year =         "2016",
  abstract =     "We consider the problem of generating compact
                 sub-optimal game-playing heuristics that can be
                 understood and easily executed by novices. In
                 particular, we seek to find heuristics that can lead to
                 good play while at the same time be expressed as fast
                 and frugal trees or short decision lists. This has
                 applications in automatically generating tutorials and
                 instructions for playing games, but also in analysing
                 game design and measuring game depth. We use the
                 classic game Blackjack as a test-bed, and compare
                 condition induction with the RIPPER algorithm,
                 exhaustive-greedy search in statement space, genetic
                 programming and axis-aligned search. We find that all
                 of these methods can find compact well-playing
                 heuristics under the given constraints, with
                 axis-aligned search performing particularly well.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CIG.2016.7860407",
  month =        sep,
  notes =        "Also known as \cite{7860407}",

Genetic Programming entries for Fernando de Mesentier Silva Aaron Isaksen Julian Togelius Andy Nealen