Genetic Programming Bibliography entries for Josh C Bongard

up to index Created by W.Langdon from gp-bibliography.bib Revision:1.8120

GP coauthors/coeditors: Amanda Bertschinger, James Bagrow, Christian Blum, Enrique Alba, Anne Auger, Jaume Bacardit, Jurgen Branke, Nicolas Bredeche, Dimo Brockhoff, Francisco Chicano, Alan Dorin, Rene Doursat, Aniko Ekart, Tobias Friedrich, Mario Giacobini, Mark Harman, Hitoshi Iba, Christian Igel, Thomas Jansen, Tim Kovacs, Taras Kowaliw, Manuel Lopez-Ibanez, Jose A Lozano, Gabriel Luque, John A W McCall, Alberto Moraglio, Alison A Motsinger, Frank Neumann, Gabriela Ochoa, Gustavo Olague, Yew-Soon Ong, Michael E Palmer, Gisele L Pappa, Konstantinos E Parsopoulos, Thomas Schmickl, Stephen L Smith, Christine Solnon, Thomas Stuetzle, El-Ghazali Talbi, Daniel R Tauritz, Leonardo Vanneschi, Hod Lipson, Anuradha Kodali, Marcin Szubert, Kamalika Das, Sangram Ganguly, Martin Pelikan, Dirk V Arnold, Anthony Brabazon, Martin V Butz, Jeff Clune, Myra B Cohen, Kalyanmoy Deb, Andries P Engelbrecht, Natalio Krasnogor, Julian F Miller, Michael O'Neill, Kumara Sastry, Dirk Thierens, Jano I van Hemert, Carsten Witt, David Buckingham, Christian Skalka, Nathan Gaylinn, Ilknur Icke, Nicholas A Allgaier, Christopher M Danforth, Robert A Whelan, Hugh P Garavan, Sam Kriegman, Hans-Georg Beyer, John A Clark, Dave Cliff, Clare Bates Congdon, Benjamin Doerr, Sanjeev Kumar, Jason H Moore, Riccardo Poli, Kenneth O Stanley, Richard A Watson, Ingo Wegener, Afsoon Yousefi Zowj,

Genetic Programming Articles by Josh C Bongard

  1. David Buckingham and Christian Skalka and Josh Bongard. Inductive machine learning for improved estimation of catchment-scale snow water equivalent. Journal of Hydrology, 524:311-325, 2015. details

  2. Josh C. Bongard. Innocent Until Proven Guilty: Reducing Robot Shaping from Polynomial to Linear Time. IEEE Transactions on Evolutionary Computation, 15(4):571-585, 2011. details

  3. Josh C. Bongard. Accelerating Self-Modeling in Cooperative Robot Teams. IEEE Transactions on Evolutionary Computation, 13(2):321-332, 2009. details

  4. Josh Bongard and Hod Lipson. Automated reverse engineering of nonlinear dynamical systems. PNAS, Proceedings of the National Academy of Sciences of the United States of America, 104(24):9943-9948, 2007. details

Genetic Programming Conference proceedings edited by Josh C Bongard

Genetic Programming conference papers by Josh C Bongard

  1. Nathan Gaylinn and Joshua Bongard. A Meta-Evolutionary Algorithm for Co-evolving Genotypes and Genotype / Phenotype Maps. In Alberto Moraglio and James McDermott editors, Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion, pages 467-470, Melbourne, Australia, 2024. Association for Computing Machinery. details

  2. Amanda Bertschinger and James Bagrow and Joshua Bongard. Evolving Form and Function: Dual-Objective Optimization in Neural Symbolic Regression Networks. In Jean-Baptiste Mouret and Kai Qin and Julia Handl and Xiaodong Li and Markus Wagner and Mario Garza-Fabre and Kate Smith-Miles and Richard Allmendinger and Ying Bi and Grant Dick and Amir H Gandomi and Marcella Scoczynski Ribeiro Martins and Hirad Assimi and Nadarajen Veerapen and Yuan Sun and Mario Andres Munyoz and Ahmed Kheiri and Nguyen Su and Dhananjay Thiruvady and Andy Song and Frank Neumann and Carla Silva editors, Proceedings of the 2024 Genetic and Evolutionary Computation Conference, pages 277-285, Melbourne, Australia, 2024. Association for Computing Machinery. details

  3. Anuradha Kodali and Marcin Szubert and Kamalika Das and Sangram Ganguly and Josh Bongard. Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis. In Anne Auger and Carlos M. Fonseca and Nuno Lourenco and Penousal Machado and Luis Paquete and Darrell Whitley editors, 15th International Conference on Parallel Problem Solving from Nature, volume 11101, pages 525-536, Coimbra, Portugal, 2018. Springer. details

  4. Marcin Szubert and Anuradha Kodali and Sangram Ganguly and Kamalika Das and Josh C. Bongard. Semantic Forward Propagation for Symbolic Regression. In Julia Handl and Emma Hart and Peter R. Lewis and Manuel Lopez-Ibanez and Gabriela Ochoa and Ben Paechter editors, 14th International Conference on Parallel Problem Solving from Nature, volume 9921, pages 364-374, Edinburgh, 2016. Springer. details

  5. Marcin Szubert and Anuradha Kodali and Sangram Ganguly and Kamalika Das and Joshua Bongard. Reducing Antagonism between Behavioral Diversity and Fitness in Semantic Genetic Programming. In Tobias Friedrich editor, GECCO '16: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 797-804, Denver, USA, 2016. ACM. details

  6. Sam Kriegman and Marcin Szubert and Josh C. Bongard and Christian Skalka. Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling. In Julia Handl and Emma Hart and Peter R. Lewis and Manuel Lopez-Ibanez and Gabriela Ochoa and Ben Paechter editors, 14th International Conference on Parallel Problem Solving from Nature, volume 9921, pages 707-716, Edinburgh, 2016. Springer. details

  7. Afsoon Yousefi Zowj and Josh C. Bongard and Christian Skalka. A Genetic Programming Approach to Cost-Sensitive Control in Resource Constrained Sensor Systems. In Sara Silva and Anna I Esparcia-Alcazar and Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and Christine Zarges and Luis Correia and Terence Soule and Mario Giacobini and Ryan Urbanowicz and Youhei Akimoto and Tobias Glasmachers and Francisco Fernandez de Vega and Amy Hoover and Pedro Larranaga and Marta Soto and Carlos Cotta and Francisco B. Pereira and Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and Heike Trautmann and Jean-Baptiste Mouret and Sebastian Risi and Ernesto Costa and Oliver Schuetze and Krzysztof Krawiec and Alberto Moraglio and Julian F. Miller and Pawel Widera and Stefano Cagnoni and JJ Merelo and Emma Hart and Leonardo Trujillo and Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and Carola Doerr editors, GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, pages 1295-1302, Madrid, Spain, 2015. ACM. details

  8. Ilknur Icke and Joshua Bongard. Improving Genetic Programming Based Symbolic Regression Using Deterministic Machine Learning. In Luis Gerardo de la Fraga editor, 2013 IEEE Conference on Evolutionary Computation, volume 1, pages 1763-1770, Cancun, Mexico, 2013. details

  9. Ilknur Icke and Joshua Bongard. Modeling Hierarchy Using Symbolic Regression. In Luis Gerardo de la Fraga editor, 2013 IEEE Conference on Evolutionary Computation, volume 1, pages 2980-2987, Cancun, Mexico, 2013. details

  10. Josh C. Bongard. A probabilistic functional crossover operator for genetic programming. In Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano van Hemert and Leonardo Vanneschi and Carsten Witt editors, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 925-932, Portland, Oregon, USA, 2010. ACM. details

  11. Josh C. Bongard. The Legion System: A Novel Approach to Evolving Heterogeneity for Collective Problem Solving. In Riccardo Poli and Wolfgang Banzhaf and William B. Langdon and Julian F. Miller and Peter Nordin and Terence C. Fogarty editors, Genetic Programming, Proceedings of EuroGP'2000, volume 1802, pages 16-28, Edinburgh, 2000. Springer-Verlag. details

  12. Josh C. Bongard. Coevolutionary Dynamics of a Multi-population Genetic Programming System. In D. Floreano and J.-D. Nicoud and F. Mondada editors, Advances in Artificial Life, volume 1674, page 154, Lausanne, 1999. Springer Verlag. details

Genetic Programming book chapters by Josh C Bongard

Genetic Programming other entries for Josh C Bongard