Abstract
In order to generate complete games through evolution we need generic and reliably evaluation functions for games. It has been suggested that game quality could be characterised through playing a game with different controllers and comparing their performance. This paper explores that idea through investigating the relative performance of different general game-playing algorithms. Seven game-playing algorithms was used to play several hand-designed, mutated and randomly generated VGDL game descriptions. Results discussed appear to support the conjecture that well-designed games have, in average, a higher performance difference between better and worse game-playing algorithms.
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Notes
- 1.
See [9] for a discussion of game-rule representation choices.
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Acknowledgments
Gabriella A.B. Barros acknowledges financial support from CAPES Scholarship and Science Without Borders program, Bex 1372713-3. Thanks to Diego Perez, Spyros Samothrakis, Tom Schaul, and Simon Lucas for useful discussions.
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Nielsen, T.S., Barros, G.A.B., Togelius, J., Nelson, M.J. (2015). General Video Game Evaluation Using Relative Algorithm Performance Profiles. In: Mora, A., Squillero, G. (eds) Applications of Evolutionary Computation. EvoApplications 2015. Lecture Notes in Computer Science(), vol 9028. Springer, Cham. https://doi.org/10.1007/978-3-319-16549-3_30
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