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In this study, we provide theoretical evidence that scalar fitness, inherently incapable of capturing such differences, is likely to lead to premature convergence. To mitigate this problem, we propose disco, a method that automatically identifies the groups of tests for which the candidate solutions behave similarly and define the above skills. Each such group gives rise to a derived objective, and these objectives together guide the search algorithm in multi-objective fashion. When applied to several well-known test-based problems, the proposed approach significantly outperforms the conventional two-population coevolution. This opens the door to efficient and generic countermeasures to premature convergence for both coevolutionary and evolutionary algorithms applied to problems featuring aggregating fitness functions.<\/jats:p>","DOI":"10.1162\/evco_a_00179","type":"journal-article","created":{"date-parts":[[2016,3,8]],"date-time":"2016-03-08T19:02:40Z","timestamp":1457463760000},"page":"375-406","source":"Crossref","is-referenced-by-count":8,"title":["Online Discovery of Search Objectives for Test-Based Problems"],"prefix":"10.1162","volume":"25","author":[{"given":"Pawe\u0142","family":"Liskowski","sequence":"first","affiliation":[{"name":"Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60965 Pozna\u0144, Poland"}]},{"given":"Krzysztof","family":"Krawiec","sequence":"additional","affiliation":[{"name":"Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60965 Pozna\u0144, Poland"}]}],"member":"281","reference":[{"key":"B1","first-page":"1","volume-title":"The dynamics of norms","author":"Axelrod R.","year":"1997"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1126\/science.7466396"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1023\/A:1015059928466"},{"issue":"3","key":"B4","first-page":"166","volume":"4","author":"Blair A. 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