When novelty is not enough
Inhaltsverzeichnis
Referenz
Cuccu, G., Gomez, F.: When novelty is not enough. In: Di Chio, C., et al. (eds.) EvoApplications 2011, Part I. LNCS, vol. 6624, pp. 234–243. Springer, Heidelberg (2011)
DOI
http://dx.doi.org/10.1007/978-3-642-20525-5_24
Abstract
The idea of evolving novel rather than fit solutions has recently been offered as a way to automatically discover the kind of complex solutions that exhibit truly intelligent behavior. So far, novelty search has only been studied in the context of problems where the number of possible “different” solutions has been limited. In this paper, we show, using a task with a much larger solution space, that selecting for novelty alone does not offer an advantage over fitness-based selection. In addition, we examine how the idea of novelty search can be used to sustain diversity and improve the performance of standard, fitness-based search.
Extended Abstract
Bibtex
@Inbook{Cuccu2011,
author="Cuccu, Giuseppe
and Gomez, Faustino",
editor="Di Chio, Cecilia
and Cagnoni, Stefano
and Cotta, Carlos
and Ebner, Marc
and Ek{\'a}rt, Anik{\'o}
and Esparcia-Alc{\'a}zar, Anna I.
and Merelo, Juan J.
and Neri, Ferrante
and Preuss, Mike
and Richter, Hendrik
and Togelius, Julian
and Yannakakis, Georgios N.",
title="When Novelty Is Not Enough",
bookTitle="Applications of Evolutionary Computation: EvoApplications 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, Torino, Italy, April 27-29, 2011, Proceedings, Part I",
year="2011",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="234--243",
isbn="978-3-642-20525-5",
doi="10.1007/978-3-642-20525-5_24",
url="http://dx.doi.org/10.1007/978-3-642-20525-5_24 http://de.evo-art.org/index.php?title=When_novelty_is_not_enough"
}
Used References
1. De Jong, K.A.: An Analysis of the Behavior of a Class of Genetic Adaptive Systems. Ph.D. thesis, The University of Michigan, Ann Arbor, MI (1975), university Microfilms No. 76-09381
2. Glover, F., Laguna, M.: Tabu Search. Kluwer Academic Publishers, Dordrecht (1997)MATH
3. Goldberg, D.E., Richardson, J.: Genetic algorithms with sharing for multimodal function optimization. In: Grefenstette, J.J. (ed.) Proceedings of the Second International Conference on Genetic Algorithms, pp. 148–154. Morgan Kaufmann, San Francisco (1987)
4. Gomez, F.: Sustaining diversity using behavioral information distance. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 113–120 (2009)
5. Krause, A., Guestrin, C.: Nonmyopic active learning of gaussian processes: An exploration- exploitation approach. In: Proceedings of the International Conference on Machine Learning (2007)
6. Lehman, J., Stanley, K.: Abandoning objectives: Evolution through the search for novelty alone. To appear in: Evolutionary Computation Journal (2010)
7. Lehman, J., Stanley, K.O.: Exploiting open-endedness to solve problems through the search for novelty. In: Proceedings of the Eleventh International Conference on Artificial Life (ALIFE XI). MIT Press, Cambridge (2008)
8. Lehman, J., Stanley, K.O.: Efficiently evolving programs through the search for novelty. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2010 (2010)
9. Lehman, J., Stanley, K.O.: Revising the evolutionary computation abstraction: minimal criteria novelty search. In: Proceedings of the Genetic and Evolutionary Computation (GECCO 2010), pp. 103–110. ACM, New York (2010)
10. MacKay, D.J.C.: Information-based objective functions for active data selection. neural computation. Neural Computation 4, 550–604 (1992)
11. Risi, S., Vanderbleek, S.D., Hughes, C.E., Stanley, K.O.: How novelty search escapes the deceptive trap of learning to learn. In: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO 2009), pp. 153–160. ACM, New York (2009) http://dx.doi.org/10.1145/1569901.1569923
12. Schmidhuber, J.: Curious model-building control systems. In: Proceedings of the International Joint Conference on Neural Networks, Singapore, vol. 2, pp. 1458–1463. IEEE press, Los Alamitos (1991)
13. Schmidhuber, J.: Developmental robotics, optimal articial curiosity, creativity, music, and the fine arts. Connection Science 18, 173–187 (2006) http://dx.doi.org/10.1080/09540090600768658
14. Teller, A.: Advances in Genetic Programming, ch. 9. MIT Press, Cambridge (1994)
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