Generating heuristics for novice players
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- @InProceedings{deMesentierSilva:2016:CIG,
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author = "Fernando {de Mesentier Silva} and Aaron Isaksen and
Julian Togelius and Andy Nealen",
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booktitle = "2016 IEEE Conference on Computational Intelligence and
Games (CIG)",
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title = "Generating heuristics for novice players",
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year = "2016",
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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.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/CIG.2016.7860407",
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month = sep,
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notes = "Also known as \cite{7860407}",
- }
Genetic Programming entries for
Fernando de Mesentier Silva
Aaron Isaksen
Julian Togelius
Andy Nealen
Citations