Kenneth O. Stanley

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Joel LehmanCarperAIVerified email at stability.ai
Risto MiikkulainenProfessor of Computer Science, the University of Texas at AustinVerified email at cs.utexas.edu
Jeff CluneCS Assoc. Professor, U. British Columbia; CIFAR AI Chair, Vector; Senior Research Advisor, DeepMindVerified email at ubc.ca
Sebastian RisiProfessor, IT University of CopenhagenVerified email at itu.dk
David B. D'AmbrosioGoogleVerified email at eecs.ucf.edu
Jason GauciEngineering Director, Argo AIVerified email at argo.ai
Lisa B. SorosRoman Family Teaching and Research Fellow, Barnard CollegeVerified email at barnard.edu
Justin K. PughUniversity of Central FloridaVerified email at cs.ucf.edu
Paul SzerlipGraduate Research Assistant, University of Central FloridaVerified email at knights.ucf.edu
Bobby D. BryantUniversity of Nevada, RenoVerified email at unr.edu
Erin HastingsUniversity of Central FloridaVerified email at alionscience.com
Amy K. HooverAssistant Professor of Informatics at New Jersey Institute of TechnologyVerified email at njit.edu
Julian TogeliusAssociate Professor of Computer Science and Engineering, New York University; co-founder, modl.aiVerified email at nyu.edu
Georgios N. YannakakisProfessor, Director, Inst. of Digital Games, University of Malta | modl.aiVerified email at um.edu.mt
Igor V. KarpovGraduate Student, The University of Texas at AustinVerified email at cs.utexas.edu
Charles OfriaMichigan State UniversityVerified email at cse.msu.edu
Phillip VerbancsicsGoogleVerified email at knights.ucf.edu
Andrea SoltoggioComputer Science Department, Loughborough UniversityVerified email at lboro.ac.uk
Joseph ReisingerThe University of Texas at AustinVerified email at cs.utexas.edu
Charlie HughesProfessor of Computer Science, University of Central FloridaVerified email at ucf.edu

Kenneth O. Stanley

Research Manager, OpenAI

Verified email at openai.com - Homepage

Artificial Intelligence Neuroevolution Neural Networks Evolutionary Computation Artificial Life


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Evolving neural networks through augmenting topologies KO Stanley, R Miikkulainen Evolutionary computation 10 (2), 99-127, 2002	4020	2002
Abandoning objectives: Evolution through the search for novelty alone J Lehman, KO Stanley Evolutionary computation 19 (2), 189-223, 2011	1000	2011
A hypercube-based encoding for evolving large-scale neural networks KO Stanley, DB D'Ambrosio, J Gauci Artificial life 15 (2), 185-212, 2009	958	2009
Compositional pattern producing networks: A novel abstraction of development KO Stanley Genetic programming and evolvable machines 8, 131-162, 2007	819	2007
Search-based procedural content generation: A taxonomy and survey J Togelius, GN Yannakakis, KO Stanley, C Browne IEEE Transactions on Computational Intelligence and AI in Games 3 (3), 172-186, 2011	814	2011
Deep neuroevolution: Genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning FP Such, V Madhavan, E Conti, J Lehman, KO Stanley, J Clune arXiv preprint arXiv:1712.06567, 2017	718	2017
Exploiting open-endedness to solve problems through the search for novelty. J Lehman, KO Stanley ALIFE, 329-336, 2008	613	2008
A taxonomy for artificial embryogeny KO Stanley, R Miikkulainen Artificial life 9 (2), 93-130, 2003	592	2003
Efficient reinforcement learning through evolving neural network topologies KO Stanley, R Miikkulainen Proceedings of the 4th Annual Conference on genetic and evolutionary …, 2002	556*	2002
Designing neural networks through neuroevolution KO Stanley, J Clune, J Lehman, R Miikkulainen Nature Machine Intelligence 1 (1), 24-35, 2019	544	2019
Competitive coevolution through evolutionary complexification KO Stanley, R Miikkulainen Journal of artificial intelligence research 21, 63-100, 2004	535	2004
Real-time neuroevolution in the NERO video game KO Stanley, BD Bryant, R Miikkulainen IEEE transactions on evolutionary computation 9 (6), 653-668, 2005	509	2005
Evolving a diversity of virtual creatures through novelty search and local competition J Lehman, KO Stanley Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011	424	2011
Quality diversity: A new frontier for evolutionary computation JK Pugh, LB Soros, KO Stanley Frontiers in Robotics and AI, 40, 2016	382	2016
Efficient reinforcement learning through evolving neural network topologies KO Stanley, R Miikkulainen Proceedings of the Genetic and Evolutionary Computation Conference (GECCO …, 2002	373	2002
Efficient reinforcement learning through evolving neural network topologies KO Stanley, R Miikkulainen Proceedings of the Genetic and Evolutionary Computation Conference (GECCO …, 2002	373	2002
Go-explore: a new approach for hard-exploration problems A Ecoffet, J Huizinga, J Lehman, KO Stanley, J Clune arXiv preprint arXiv:1901.10995, 2019	347	2019
Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents E Conti, V Madhavan, F Petroski Such, J Lehman, K Stanley, J Clune Advances in neural information processing systems 31, 2018	339	2018
Efficient evolution of neural networks through complexification KO Stanley University of Texas at Austin, 2004	266	2004
Picbreeder: evolving pictures collaboratively online J Secretan, N Beato, DB D Ambrosio, A Rodriguez, A Campbell, ... Proceedings of the SIGCHI conference on human factors in computing systems …, 2008	242	2008

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