Genetic Programming Bibliography entries for Dirk Schweim
up to index
Created by W.Langdon from
Genetic Programming Articles by Dirk Schweim
Genetic Programming conference papers by Dirk Schweim
Dirk Schweim and Erik Hemberg and Dominik Sobania and Una-May O'Reilly.
Exploiting Knowledge from Code to Guide Program Search. In
Eric Medvet and Gisele Pappa and Bing Xue editors,
EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, volume 13223, pages 262-277, Madrid, Spain, 2022. Springer Verlag.
Dirk Schweim and David Wittenberg and Franz Rothlauf.
On Sampling Error in Evolutionary Algorithms. In
Carola Doerr editor,
Proceedings of the 2021 Genetic and Evolutionary Computation Conference, pages 43-44, internet, 2021. Association for Computing Machinery.
Dirk Schweim and Erik Hemberg and Dominik Sobania and Una-May O'Reilly and Franz Rothlauf.
Using Knowledge of Human-Generated Code to Bias the Search in Program Synthesis with Grammatical Evolution. In
Francisco Chicano and Alberto Tonda and Krzysztof Krawiec and Marde Helbig and Christopher W. Cleghorn and Dennis G. Wilson and Georgios Yannakakis and Luis Paquete and Gabriela Ochoa and Jaume Bacardit and Christian Gagne and Sanaz Mostaghim and Laetitia Jourdan and Oliver Schuetze and Petr Posik and Carlos Segura and Renato Tinos and Carlos Cotta and Malcolm Heywood and Mengjie Zhang and Leonardo Trujillo and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Fuyuki Ishikawa and Inmaculada Medina-Bulo and Frank Neumann and Andrew M. Sutton editors,
Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion, pages 331-332, internet, 2021. Association for Computing Machinery.
On the Influence of Grammars on Crossover in Grammatical Evolution. In
Ting Hu and Nuno Lourenco and Eric Medvet editors,
EuroGP 2021: Proceedings of the 24th European Conference on Genetic Programming, volume 12691, pages 114-129, Virtual Event, 2021. Springer Verlag.
David Wittenberg and Franz Rothlauf and Dirk Schweim.
DAE-GP: Denoising Autoencoder LSTM Networks as Probabilistic Models in Estimation of Distribution Genetic Programming. In
Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors,
Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 1037-1045, internet, 2020. Association for Computing Machinery.
Genetic Programming book chapters by Dirk Schweim