Parallel Problem Solving From Nature, PPSN XI 2010
DOI: 10.1007/978-3-642-15871-1_8
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Towards Directed Open-Ended Search by a Novelty Guided Evolution Strategy

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Cited by 5 publications
(3 citation statements)
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“…The benefits of divergent search were further confirmed through similar experiments by Mouret and Doncieux (2009) and Mouret and Doncieux (2012), who use the synonymous term behavioral diversity. These initial studies were followed by a wave of interest in divergent search algorithms as researchers explored their potential for discovery and open-endedness (Risi et al, 2009(Risi et al, , 2011Soltoggio and Jones, 2009;Doucette and Heywood, 2010;Goldsby and Cheng, 2010;Graening et al, 2010;Krcah, 2010;Kistemaker and Whiteson, 2011;Woolley and Stanley, 2011;Liapis et al, 2013a,b;Martinez et al, 2013;Morse et al, 2013;Naredo and Trujillo, 2013;Risi and Stanley, 2013). However, a clear missing ingredient from pure novelty or behavioral diversity techniques is a complementary notion of objective quality.…”
Section: Early Divergent Search Algorithmsmentioning
confidence: 99%
“…The benefits of divergent search were further confirmed through similar experiments by Mouret and Doncieux (2009) and Mouret and Doncieux (2012), who use the synonymous term behavioral diversity. These initial studies were followed by a wave of interest in divergent search algorithms as researchers explored their potential for discovery and open-endedness (Risi et al, 2009(Risi et al, , 2011Soltoggio and Jones, 2009;Doucette and Heywood, 2010;Goldsby and Cheng, 2010;Graening et al, 2010;Krcah, 2010;Kistemaker and Whiteson, 2011;Woolley and Stanley, 2011;Liapis et al, 2013a,b;Martinez et al, 2013;Morse et al, 2013;Naredo and Trujillo, 2013;Risi and Stanley, 2013). However, a clear missing ingredient from pure novelty or behavioral diversity techniques is a complementary notion of objective quality.…”
Section: Early Divergent Search Algorithmsmentioning
confidence: 99%
“…This is, for example, done by relying on novelty alone to select relevant solutions and steer the optimization into the desired direction [12], by combining novelty and a local competition factor of the considered solutions [13], or restarting the optimization based on a novelty-score [14]. Furthermore, additional derived measures such as the interestingness [15,16] or the curiosity [17] can be considered in addition to performance criteria.…”
Section: Optimization-based Approachesmentioning
confidence: 99%
“…Historically, a small community within the field of artificial life (Brant & Stanley, 2017;Graening et al, 2010;Langdon, 2005;Lehman & Stanley, 2008;Ray, 1991;Soros & Stanley, 2014;Soros et al, 2016;Standish, 2003b;Stanley et al, 2017;Taylor et al, 2016) has studied the prospects of openended computation for many years. In the ongoing multipronged quest in pursuit of powerful AI, open-endedness is a critical prong: it could serve to generate training environments for meta-learning algorithms (Duan et al, 2016;Finn et al, 2017;Wang et al, 2016), and eventually act as a stepping stone towards AI-generating algorithms (AI-GAs) that could one day bootstrap themselves from simple initial conditions to powerful cognitive machines.…”
Section: Related Workmentioning
confidence: 99%