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DC Field | Value | Language |
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dc.contributor.author | Liapis, Antonios | - |
dc.contributor.author | Yannakakis, Georgios N. | - |
dc.contributor.author | Togelius, Julian | - |
dc.date.accessioned | 2018-05-03T09:38:07Z | - |
dc.date.available | 2018-05-03T09:38:07Z | - |
dc.date.issued | 2013-07 | - |
dc.identifier.citation | Liapis, A., Yannakakis, G. N., & Togelius, J. (2013). Enhancements to constrained novelty search: Two-population novelty search for generating game content. Fifteenth Annual Conference on Genetic and Evolutionary Computation, Amsterdam. 343-350. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/29732 | - |
dc.description.abstract | Novelty search is a recent algorithm geared to explore search spaces without regard to objectives; minimal criteria novelty search is a variant of this algorithm for constrained search spaces. For large search spaces with multiple constraints, however, it is hard to find a set of feasible individuals that is both large and diverse. In this paper, we present two new methods of novelty search for constrained spaces, Feasible-Infeasible Novelty Search and Feasible-Infeasible Dual Novelty Search. Both algorithms keep separate populations of feasible and infeasible individuals, inspired by the FI-2pop genetic algorithm. These algorithms are applied to the problem of creating diverse and feasible game levels, representative of a large class of important problems in procedural content generation for games. Results show that the new algorithms under certain conditions can produce larger and more diverse sets of feasible strategy game maps than existing algorithms. However, the best algorithm is contingent on the particularities of the search space and the genetic operators used. It is also shown that the proposed enhancement of offspring boosting increases performance in all cases. | en_GB |
dc.description.sponsorship | The research is supported, in part, by the FP7 ICT project SIREN (project no: 258453) and by the FP7 ICT project C2Learn (project no: 318480). | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | GECCO | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | Evolutionary computation | en_GB |
dc.subject | Gentic algorithms | en_GB |
dc.subject | Computer games -- Design | en_GB |
dc.title | Enhancements to constrained novelty search : two-population novelty search for generating game content | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.bibliographicCitation.conferencename | Fifteenth Annual Conference on Genetic and Evolutionary Computation (GECCO) 2013 | en_GB |
dc.bibliographicCitation.conferenceplace | Amsterdam, Netherlands, 06-10/07/2013 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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Enhancements_to_constrained_novelty_search_two-population_novelty_search_for_2013.pdf | 1.11 MB | Adobe PDF | View/Open |
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