HyperNEAT

• Multi-agent learning{{Cite book|last1=D'Ambrosio|first1=David B.|last2=Stanley|first2=Kenneth O.|title=Proceedings of the 10th annual conference on Genetic and evolutionary computation |chapter=Generative encoding for multiagent learning |date=2008-01-01|series=GECCO '08|location=New York, NY, USA|publisher=ACM|pages=819–826|doi=10.1145/1389095.1389256|isbn=9781605581309|s2cid=11507017}}
• Checkers board evaluationJ. Gauci and K. O. Stanley, “A case study on the critical role of geometric regularity in machine learning,” in AAAI (D. Fox and C. P. Gomes, eds.), pp. 628–633, AAAI Press, 2008.
• Controlling Legged Robots{{Cite book|last1=Risi|first1=Sebastian|last2=Stanley|first2=Kenneth O.|title=Proceedings of the 15th annual conference on Genetic and evolutionary computation |chapter=Confronting the challenge of learning a flexible neural controller for a diversity of morphologies |date=2013-01-01|series=GECCO '13|location=New York, NY, USA|publisher=ACM|pages=255–262|doi=10.1145/2463372.2463397|isbn=9781450319638|citeseerx=10.1.1.465.5068|s2cid=10308013}}{{Cite book|last1=Clune|first1=J.|last2=Beckmann|first2=B. E.|last3=Ofria|first3=C.|last4=Pennock|first4=R. T.|title=2009 IEEE Congress on Evolutionary Computation |chapter=Evolving coordinated quadruped gaits with the HyperNEAT generative encoding |date=2009-05-01|pages=2764–2771|doi=10.1109/CEC.2009.4983289|isbn=978-1-4244-2958-5|citeseerx=10.1.1.409.3868|s2cid=17566887}}{{Cite book|last1=Clune|first1=Jeff|last2=Ofria|first2=Charles|last3=Pennock|first3=Robert T.|title=Proceedings of the 11th Annual conference on Genetic and evolutionary computation |chapter=The sensitivity of HyperNEAT to different geometric representations of a problem |date=2009-01-01|series=GECCO '09|location=New York, NY, USA|publisher=ACM|pages=675–682|doi=10.1145/1569901.1569995|isbn=9781605583259|s2cid=16054567}}Yosinski J, Clune J, Hidalgo D, Nguyen S, Cristobal Zagal J, Lipson H (2011) Evolving Robot Gaits in Hardware: the HyperNEAT Generative Encoding Vs. Parameter Optimization. Proceedings of the European Conference on Artificial Life. ([http://jeffclune.com/publications/2011-YosinskiEtAl-EvolvingRoboticGaitsInHardware-ECAL.pdf pdf])Lee S, Yosinski J, Glette K, Lipson H, Clune J (2013) Evolving gaits for physical robots with the HyperNEAT generative encoding: the benefits of simulation. Applications of Evolutionary Computing. Springer. [http://jeffclune.com/publications/2013-LeeEtal-HyperNEAT+Sim.pdf pdf]{{Cite book|title=Applications of Evolutionary Computation|last1=Lee|first1=Suchan|last2=Yosinski|first2=Jason|last3=Glette|first3=Kyrre|last4=Lipson|first4=Hod|last5=Clune|first5=Jeff|chapter=Evolving Gaits for Physical Robots with the HyperNEAT Generative Encoding: The Benefits of Simulation |date=2013-04-03|publisher=Springer Berlin Heidelberg|isbn=9783642371912|editor-last=Esparcia-Alcázar|editor-first=Anna I.|series=Lecture Notes in Computer Science|volume=7835 |pages=540–549|language=en|doi=10.1007/978-3-642-37192-9_54|citeseerx = 10.1.1.364.8979}}[https://www.youtube.com/watch?v=V2ADU8YWIug video]
• Comparing Generative vs. Direct Encodings{{Cite journal|last1=Clune|first1=J.|last2=Stanley|first2=K. O.|last3=Pennock|first3=R. T.|last4=Ofria|first4=C.|date=2011-06-01|title=On the Performance of Indirect Encoding Across the Continuum of Regularity|journal=IEEE Transactions on Evolutionary Computation|volume=15|issue=3|pages=346–367|doi=10.1109/TEVC.2010.2104157|issn=1089-778X|citeseerx=10.1.1.375.6731|s2cid=3008628}}{{Cite book|title=Parallel Problem Solving from Nature – PPSN X|last1=Clune|first1=Jeff|last2=Ofria|first2=Charles|last3=Pennock|first3=Robert T.|chapter=How a Generative Encoding Fares as Problem-Regularity Decreases |date=2008-09-13|publisher=Springer Berlin Heidelberg|isbn=9783540876991|editor-last=Rudolph|editor-first=Günter|series=Lecture Notes in Computer Science|volume=5199 |pages=358–367|language=en|doi=10.1007/978-3-540-87700-4_36|editor-last2=Jansen|editor-first2=Thomas|editor-last3=Beume|editor-first3=Nicola|editor-last4=Lucas|editor-first4=Simon|editor-last5=Poloni|editor-first5=Carlo}}{{Cite book|title=Advances in Artificial Life. Darwin Meets von Neumann|last1=Clune|first1=Jeff|last2=Beckmann|first2=Benjamin E.|last3=Pennock|first3=Robert T.|last4=Ofria|first4=Charles|chapter=HybrID: A Hybridization of Indirect and Direct Encodings for Evolutionary Computation |date=2009-09-13|publisher=Springer Berlin Heidelberg|isbn=9783642213137|editor-last=Kampis|editor-first=George|series=Lecture Notes in Computer Science|volume=5778 |pages=134–141|language=en|doi=10.1007/978-3-642-21314-4_17|editor-last2=Karsai|editor-first2=István|editor-last3=Szathmáry|editor-first3=Eörs|citeseerx = 10.1.1.409.741}}
• Investigating the Evolution of Modular Neural Networks{{Cite book|last1=Clune|first1=Jeff|last2=Beckmann|first2=Benjamin E.|last3=McKinley|first3=Philip K.|last4=Ofria|first4=Charles|title=Proceedings of the 12th annual conference on Genetic and evolutionary computation |chapter=Investigating whether hyperNEAT produces modular neural networks |date=2010-01-01|series=GECCO '10|location=New York, NY, USA|publisher=ACM|pages=635–642|doi=10.1145/1830483.1830598|isbn=9781450300728|citeseerx=10.1.1.409.4870|s2cid=14826185}}{{Cite book|last1=Suchorzewski|first1=Marcin|last2=Clune|first2=Jeff|title=Proceedings of the 13th annual conference on Genetic and evolutionary computation |chapter=A novel generative encoding for evolving modular, regular and scalable networks |date=2011-01-01|series=GECCO '11|location=New York, NY, USA|publisher=ACM|pages=1523–1530|doi=10.1145/2001576.2001781|isbn=9781450305570|citeseerx=10.1.1.453.5744|s2cid=2542736}}{{Cite book|last1=Verbancsics|first1=Phillip|last2=Stanley|first2=Kenneth O.|title=Proceedings of the 13th annual conference on Genetic and evolutionary computation |chapter=Constraining connectivity to encourage modularity in HyperNEAT |date=2011-01-01|series=GECCO '11|location=New York, NY, USA|publisher=ACM|pages=1483–1490|doi=10.1145/2001576.2001776|isbn=9781450305570|citeseerx=10.1.1.379.1188|s2cid=1442181}}
• Evolving Objects that can be 3D-printed{{Cite journal|last1=Clune|first1=Jeff|last2=Lipson|first2=Hod|date=2011-11-01|title=Evolving 3D Objects with a Generative Encoding Inspired by Developmental Biology|journal=ACM SIGEVOlution|volume=5|issue=4|pages=2–12|doi=10.1145/2078245.2078246|s2cid=9566239|issn=1931-8499}}
• Evolving the Neural Geometry and Plasticity of an ANN{{Cite book|last1=Risi|first1=S.|last2=Stanley|first2=K. O.|title=The 2012 International Joint Conference on Neural Networks (IJCNN) |chapter=A unified approach to evolving plasticity and neural geometry |date=2012-06-01|pages=1–8|doi=10.1109/IJCNN.2012.6252826|isbn=978-1-4673-1490-9|citeseerx=10.1.1.467.8366|s2cid=14268194}}

{{reflist}}

• {{webarchive |url=https://web.archive.org/web/20240309224307/http://eplex.cs.ucf.edu/hyperNEATpage/HyperNEAT.html |date=2024-03-09 |title=The HyperNEAT Users Page}}
• {{webarchive |url=https://web.archive.org/web/20240205000734/http://www.cs.ucf.edu/~kstanley/ |date=2024-02-05 |title=Ken Stanley's website at UCF}}
• {{webarchive |url=https://web.archive.org/web/20240618051618/http://eplex.cs.ucf.edu/ |date=2024-06-18 |title=Evolutionary Complexity Research Group at UCF}}
• {{webarchive |url=https://web.archive.org/web/20231205130538/http://www.cs.ucf.edu/~kstanley/neat.html |date=2023-12-05 |title=The NEAT Users Page}}
• {{webarchive |url=https://web.archive.org/web/20210417053504/http://picbreeder.org/ |date=2021-04-17 |title=Picbreeder}}
• {{webarchive |url=https://web.archive.org/web/20181114121019/http://endlessforms.com/ |date=2018-11-14 |title=EndlessForms}}
• {{webarchive |url=https://web.archive.org/web/20241224160241/http://beacon-center.org/blog/2012/08/13/evolution-101-neuroevolution/ |date=2024-12-24 |title=BEACON Blog: Evolution 101: Neuroevolution}}

Category:Evolutionary algorithms and artificial neuronal networks

Category:Evolutionary computation

Category:Genetic algorithms

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