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A comment on Algorithms that select which algorithm should play which game.

Re:Algorithms that select which algorithm should play which ... by daveguy on Wednesday August 10, 2016 @06:05PM (#12265051)
On the grid graph comparison of how different algorithms perform on different games, two questions:

1) What is the source data for that plot?

2) You specify "lighter = better", but how are they normalized across games and algorithms? How is better and worse quantified to get a "lightness"?

Edit: Found #2 in the second paper. Still don't know what 25 wins is white and 0 wins is black means? How do you "win" some of these?

Two papers are here:

http://julian.togelius.com/Mendes2016HyperHeuristic.pdf

http://julian.togelius.com/Bontrager2016Matching.pdf

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Re:Algorithms that select which algorithm should play which ... by togelius on Thursday August 11, 2016 @09:09AM (#12267883)
The source of data is a lot of simulations we ran ourselves. All of the games can be won or lost - there's also a score measure as well, but that was not used in producing that graphic.
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Re:Algorithms that select which algorithm should play which ... by daveguy on Thursday August 11, 2016 @09:37AM (#12268086)
So something like digdug being black means that no algorithm has progressed through all levels to completely beat the game? That seems like a high bar to set for a "win".
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