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Book
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Refereed
conference
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Workshops
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minimally-
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Pfeifer R. and Bongard J. (2006) How the Body Shapes the Way We Think: A New View of Intelligence, MIT Press, November.
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S Kriegman, D Blackiston, M Levin, J Bongard (2020). A scalable pipeline for designing reconfigurable organisms. PNAS, 117(4): 1853-1859.
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I Rahwan, M Cebrian, N Obradovich, J Bongard, J-F Bonnefon, C Breazeal, JW Crandall, NA Christakis, ID Couzin, MO Jackson, NR Jennings, E Kamar, IM Kloumann, H Larochelle, D Lazer, R McElreath, A Mislove, DC Parkes, A Pentland, ME Roberts, A Shariff, JB Tenenbaum & M Wellman (2019).
Machine behaviour.
Nature, 568: 477486
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Rounds, T., Bongard, J., Hines, P., & Harvey, J. (2019).
A crowdsourcing approach to understand weight and weight loss in men.
Preventive Medicine Reports, 13, 224.
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S Kriegman, N Cheney, J Bongard (2018).
How morphological development can guide evolution.
Nature Scientific Reports, 8(1): 13934.
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F Corucci, N Cheney, F Giorgio-Serchi, J Bongard, and C Laschi (2018).
Evolving Soft Locomotion in Aquatic and Terrestrial Environments: Effects of Material Properties and Environmental Transitions.
Soft Robotics 5.4 (2018): 475-495.
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N Cheney, J Bongard, V SunSpiral, H Lipson (2018)
Scalable co-optimization of morphology and control in embodied machines.
Journal of The Royal Society Interface, 15(143): 20170937
A Bernatskiy, J Bongard (2018)
Evolving morphology automatically reformulates the problem of designing modular control.
Adaptive Behavior 26(2): 47-64
MD Wagy, JC Bongard, JP Bagrow, PDH Hines (2017).
Crowdsourcing predictors of residential electric energy usage.
IEEE Systems Journal, PP(99):1-10.
D Buckingham & JC Bongard (2017).
Physical Scaffolding Accelerates the Evolution of Robot Behavior.
Artificial Life, 23(3):351-373.
F Corucci, N Cheney, S Kriegman, J Bongard, C Laschi (2017).
Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants.
Frontiers in Robotics and AI.
N Livingston, A Bernatskiy, K Livingston, ML Smith, J Schwarz, JC Bongard, D Wallach & JH Long Jr (2016).
Modularity and sparsity: evolution of neural net controllers in physically embodied robots.
Frontiers in Robotics and AI.
T Taylor, JE Auerbach, J Bongard, J Clune, S Hickinbotham, C Ofria, M Oka, S Risi, KO Stanley, J Yosinski (2016).
WebAL comes of age: A review of the first 21 years of artificial life on the web.
Artificial Life, 22(3) 364-407.
CK Cappelle, A Bernatskiy, K Livingston, N Livingston, J Bongard (2016).
Morphological modularity can enable the evolution of robot behavior to scale linearly with the number of environmental features. Frontiers in Robotics and AI, frobt.2016.00059.
J Bongard (2015).
Using robots to investigate the evolution of adaptive behavior.
Current Opinion in Behavioral Sciences, 6: 168-173.
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M Wagy & J Bongard. (2015).
Combining computational and social effort for collaborative problem solving. PLoS ONE, DOI: 10.1371/journal.pone.0142524.
D Buckingham, C Skalka, and J Bongard (2015).
Inductive machine learning for improved estimation of catchment-scale snow water equivalent.
Journal of Hydrology, 524: 311-325.
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R Swain and A Berger and J Bongard and P Hines. (2015).
Participation and contribution in crowdsourced surveys.
PLoS ONE, DOI: 10.1371/journal.pone.0120521
Bongard, J.C., Lipson, H. (2014).
Evolved machines shed light on robustness and resilience.
Proceedings of the IEEE, 102(5): 899-914.
Lu, Z., Wu, X and Bongard, J. C. (2014).
Active learning through adaptive heterogeneous ensembling.
IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2014.2304474
Bevelander, K. E., Kaipainen, K., Swain, R., Dohle, S., Bongard, J. C., Hines, P. D. H., Wansink, B. (2014).
Crowdsourcing novel childhood predictors of adult obesity.
PLoS ONE DOI: 10.1371/journal.pone.0087756.
Auerbach, J. E. and Bongard, J. C. (2014). Environmental influence on the evolution of morphological complexity in machines. PLoS Computational Biology, 10(1): e1003399
Bongard J. (2013). Evolutionary robotics. Communications of the ACM 56(8): 74-85.
Bongard, J. C., Hines, P. D. H., Conger, D., Hurd, P., and Lu, Z. (2012). Crowdsourcing predictors of behavioral outcomes. IEEE Transactions on Systems, Man, and Cybernetics, Part A, DOI: 10.1109/TSMCA.2012.2195168.
Bongard J. (2011). Morphological change in machines accelerates the evolution of robust behavior. Proceedings of the National Academy of Sciences 108(4): 1234-1239.
Bongard J. C. (2011). Innocent until proven guilty: Reducing robot shaping from polynomial to linear time. IEEE Transactions on Evolutionary Computation 15(4): 571-585.
Krishnanand, K. N., Bongard, J. C., Meltzoff, A. N. (2010) Self discovery enables robot social cognition: Are you my teacher? Neural Networks, Special Issue on the Science of Learning, 23: 1113-1124.
Bongard J. C. (2010). The utility of evolving simulated robot morphology increases with task complexity for object manipulation. Artificial Life, 16(3): 201-223. [Video1] [Video2] [Video3]
Rughani, A. I., Dumont, T. M., Lu, Z., Bongard, J., Horgan, M. A., Penar, P. L., Tranmer, B. I. (2009) Use of an artificial neural network to predict head injury outcome. Journal of Neurosurgery, DOI: 10.3171/2009.11JNS09857.
Bongard J. C. (2009). Accelerating self-modeling in cooperative robot teams. IEEE Transactions on Evolutionary Computation, 13(2): 321-332.
Bongard J. and Lipson H.(2007). Automated reverse engineering of nonlinear dynamical systems. Proceedings of the National Academy of Sciences, 104(24): 9943-9948.
Bongard, J., Zykov, V., Lipson, H. (2006). Resilient machines through continuous self-modeling. Science, 314: 1118-1121.
Kouchmeshky, B., Aquino, W., Lipson, H., and Bongard, J. C. (2006). Coevolutionary strategy for structural damage identification using minimal physical testing. International Journal for Numerical Methods in Engineering, 69(5): 1085-1107.
Bongard J. and Lipson H. (2005) Active coevolutionary learning of deterministic finite automata, Journal of Machine Learning Research, 6(Oct): 1651-1678
Bongard J. and Lipson H. (2005) Nonlinear system identification using coevolution of models and tests, IEEE Transactions on Evolutionary Computation, 9(4): 361-384.
Pfeifer, R., F. Iida and J. Bongard (2005) New Robotics: Design Principles for Intelligent Systems, Artificial Life, Special Issue on New Robotics, Evolution and Embodied Cognition, 11(1-2): 99-120.
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A Cangelosi, J Bongard, MH Fischer, S Nolfi (2015) Embodied intelligence. In Springer Handbook of Computational Intelligence, pp. 697-714.
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Bongard, J. C. (2014) Evolving morphological computation. In H Hauser, RM Fuchslin, & R Pfeifer (eds.), Opinions and Outlooks on Morphological Computation ISBN: 978-3-033-04515-6.
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Bongard, J. C. (2014) Why Morphology Matters. In PA Vargas, EA Di Paolo, I Harvey & P Husbands(eds.), The Horizons of Evolutionary Robotics, 125-152.
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Icke, I., Allgaier, N. A., Danforth, C. M., Whelan, R., Garavan, H., Bongard, J. C. (2013) A Deterministic and Symbolic Regression Hybrid Applied to Resting-State fMRI data. In Genetic Programming Theory and Practice IX, Springer.
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Bongard, J. C. (2011) The `What', `How' and the `Why' of Evolutionary Robotics. In Doncieux, S., Bredeche, N., Mouret, J.-B. (eds.), New Horizons in Evolutionary Robotics (Studies in Computational Intelligence), 341: 29-35.
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Bongard, J. C. (2009) A Functional Crossover Operator for Genetic Programming. In Riolo R., O'Reilly, U.-M., McConaghy, T. (eds.),Genetic Programming Theory and Practice VII, pp. 195-210, Springer.
Bongard, J. C. and R. Pfeifer (2003) Evolving Complete Agents Using Artificial Ontogeny, in Hara, F. and R. Pfeifer, (eds.), Morpho-functional Machines: The New Species (Designing Embodied Intelligence) Springer-Verlag, pp. 237-258.
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K Rosser, J Kok, J Chahl, J Bongard (2020). Sim2real gap is non-monotonic with robot complexity for morphology-in-the-loop flapping wing design. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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S Kriegman, A-M Nasab, D Shah, H Steele, G Branin, M Levin, J Bongard, R Kramer-Bottiglio (2020). Scalable sim-to-real transfer of soft robot designs. Proceedings of the IEEE International Conference on Soft Robotics (Robosoft) .
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S Kriegman, S Walker, D Shah, M Levin, R Kramer-Bottiglio, J Bongard (2019). Automated shapeshifting for function recovery in damaged robots. RSS Conference Proceedings, pp. x-y.
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A Kodali, M Szubert, K Das, S Ganguly, J Bongard (2018). Understanding climate-vegetation interactions in global rainforests through a GP-tree analysis. PPSN Conference Proceedings, pp. 525–536
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S Beaulieu, S Kriegman, JC Bongard (2018). Combating catastrophic forgetting with developmental compression. GECCO Conference Proceedings, pp. 386–393
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S Kriegman, N Cheney, F Corucci, JC Bongard (2018). Interoceptive robustness through environment-mediated morphological development. GECCO Conference Proceedings, pp. 109–116.
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F Veenstra, PG de Prado Salas, J Bongard, K Stoy, S Risi (2018). Intrinsic Mortality Governs Evolvability. Artificial Life Conference Proceedings, pp. 242-249.
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C Cappelle, J Bongard (2018). Embodied Embeddings for Hyperneat. Artificial Life Conference Proceedings, pp. 461-468
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J Powers, S Kriegman, J Bongard (2018). The effects of morphology and fitness on catastrophic interference. Artificial Life Conference Proceedings, pp. 606-613
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A Bernatskiy & J Bongard (2017). Choice of robot morphology can prohibit modular control and disrupt evolution. Proceedings of the European Conference on Artificial Life.
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S Kriegman, N Cheney, F Corucci, JC Bongard (2017). A minimal developmental model can increase evolvability in soft robots. Proceedings of the Genetic and Evolutionary Computation Conference, pp 131-138.
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C Cappelle, A Bernatskiy, J Bongard (2017). Reducing Training Environments in Evolutionary Robotics Through Ecological Modularity. Proceedings of the Conference on Biomimetic and Biohybrid Systems, pp 95-106
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M Szubert, A Kodali, S Ganguly, K Das & JC Bongard (2016) Semantic forward propagation for symbolic regression. Proceedings of the Parallel Problem Solving from Nature (PPSN) Conference , Edinburgh, UK.
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S Kriegman, M Szubert, JC Bongard & C Skalka (2016) Evolving spatially aggregated features From satellite imagery for regional modeling. Proceedings of the Parallel Problem Solving from Nature (PPSN) Conference , Edinburgh, UK.
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N Powell & JC Bongard (2016) Exploring uncertainty and movement in categorical perception using robots. Proceedings of the Parallel Problem Solving from Nature (PPSN) Conference , Edinburgh, UK.
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M Szubert, A Kodali, S Ganguly, K Das & JC Bongard (2016) Reducing antagonism between behavioral diversity and fitness in semantic genetic programming. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016), Denver, CO.
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N Cheney, JC Bongard, V SunSpiral & H Lipson (2016) On the difficulty of co-optimizing morphology and control in evolved virtual creatures .The 15th International Conference on the Synthesis and Simulation of Living Systems (ALife 2016), Cancun, Mexico.
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F Corucci, N Cheney, H Lipson, C Laschi & JC Bongard (2016) Material properties affect evolution’s ability to exploit morphological computation in growing soft-bodied creatures. The 15th International Conference on the Synthesis and Simulation of Living Systems (ALife 2016), Cancun, Mexico.
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J Anetsberger & JC Bongard (2016) Robots can ground crowd-proposed symbols by forming theories of group mind. The 15th International Conference on the Synthesis and Simulation of Living Systems (ALife 2016), Cancun, Mexico.
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M Wagy & JC Bongard (2016) Social contribution in the design of adaptive machines on the web. The 15th International Conference on the Synthesis and Simulation of Living Systems (ALife 2016), Cancun, Mexico.
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M Wagy & JC Bongard (2015) Crowdseeding: a novel approach for designing bioinspired machines. Fourth Intl Conf on Biomimetics and Biohybrid Systems (Living Machines 2015), Barcelona, Spain.
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K Zieba & JC Bongard (2015) An embodied approach for evolving robust visual classifiers. Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain.
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A Yousefi, JC Bongard & C Skalka (2015) A Genetic Programming approach to cost-sensitive control in resource constrained sensor systems. Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain.
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N Cheney, JC Bongard & H Lipson (2015) Evolving soft robots in tight spaces. Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain.
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JC Bongard, A Bernatskiy, K Livingston, N Livingston, J Long & M Smith (2015) Evolving robot morphology facilitates the evolution of neural modularity and evolvability. Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain.
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Wagy, M., Bongard, J. C. (2014) Collective Design of Robot Locomotion. ALIFE 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems DOI:
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Bernatskiy, A., Hornby, G. S., Bongard, J. C. (2014) Improving Robot Behavior Optimization by Combining User Preferences. ALIFE 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems DOI:
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Icke, I., Bongard, J. C. (2013) Improving Genetic Programming Based Symbolic Regression Using Deterministic Machine Learning. 2013 IEEE Congress on Evolutionary Computation, Cancun, MX.
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Icke, I., Bongard, J. C. (2013) Modeling Hierarchy using Symbolic Regression. 2013 IEEE Congress on Evolutionary Computation,Cancun, MX.
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Celis, S., Hornby, G. S., Bongard, J. C. (2013) Avoiding Local Optima with User Demonstrations and Low-level Control. 2013 IEEE Congress on Evolutionary Computation, Cancun, MX.
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Bongard, J. C., Hornby, G. S. (2013) Combining Fitness-based Search and User Modeling in Evolutionary Robotics, 2013 Genetic and Evolutionary Computation Conference (GECCO 2013), pp. 159-166.
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Auerbach, J. E., Bongard, J. C. (2012) On the Relationship Between Environmental and Morphological Complexity in Evolved Robots,Proceedings of the 2012 Genetic and Evolutionary Computation Conference (GECCO 2012), pp. 521-528, DOI: 10.1145/2330163.2330238.
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Auerbach, J. E., Bongard, J. C. (2012) On the Relationship Between Environmental and Mechanical Complexity in Evolved Robots.Proceedings of the 13th International Conference on the Synthesis and Simulation of Living Systems (ALife XIII), pp. 309-316, DOI: 10.7551/978-0-262-31050-5-ch041.
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Hornby, G. S., Bongard, J. C. (2012) Accelerating Interactive Evolutionary Algorithms through Comparative and Predictive User Models,2012 Genetic and Evolutionary Computation Conference (GECCO 2012), DOI: 10.1145/2330163.2330196.
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Hornby, G. S., Bongard, J. C. (2012) Learning Comparative User Models for Accelerating Human-Computer Collaborative Search.Proceedings of the Evolutionary and Biologically Inspired Music, Sound, Art and Design, pp. 117-128, DOI: 10.1007/978-3-642-29142-5_11.
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Auerbach, J. E., Bongard, J. C. (2011) Evolving Complete Robots with CPPN-NEAT: The Utility of Recurrent Connections, 2011 Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, IR.
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Bongard, J. C. (2011) Spontaneous Evolution of Structural Modularity in Robot Neural Network Controllers. 2011 Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, IR.
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Bongard, J. C. (2011) Morphological and Environmental Scaffolding Synergize when Evolving Robot Controllers, 2011 Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, IR.
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Auerbach, J. E., Bongard, J. C. (2010) Dynamic Resolution in the Co-Evolution of Morphology and Control. 12th International Conference on the Synthesis and Simulation of Living Systems (ALife XII), Portland, OR.
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Lu, Z., Wu, X., Zhu, X., Bongard, J. (2010) Ensemble Pruning via Individual Contribution Ordering, The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Washington DC, 2010
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Auerbach, J. E., Bongard, J. C. (2010) Evolving CPPNs to Grow Three Dimensional Structures. 2010 Genetic and Evolutionary Computation Conference (GECCO 2010), Portland, OR.
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Bongard, J. C. (2010) A Probabilistic Functional Crossover Operator for Genetic Programming. 2010 Genetic and Evolutionary Computation Conference (GECCO 2010), Portland, OR.
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Bongard, J. C., Hornby, G. S. (2010) Guarding Against Premature Convergence while Accelerating Evolutionary Search. 2010 Genetic and Evolutionary Computation Conference (GECCO 2010), to appear.
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Lu, Z., Wu, X., Bongard, J. (2010) Adaptive Informative Sampling for Active Learning, The 2010 SIAM Conference on Data Mining (SDM 2010), Columbus, Ohio, USA, 2010
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Lu, Z., Wu, X., Bongard, J. (2009) Active Learning with Adaptive Heterogeneous Ensembles The 2009 IEEE International Conference on Data Mining (ICDM 2009) pages 327-336, Miami, FL.
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Kaipa, K., Bongard, J. C., Meltzoff A. N. (2009) Combined Structure and Motion Extraction from Visual Data Using Evolutionary Active Learning 2009 Genetic and Evolutionary Computation Conference (GECCO 2009), Montreal Canada.
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Auerbach, J., Bongard, J. C. (2009) Evolution of Functional Specialization in a Morphologically Homogeneous Robot. 2009 Genetic and Evolutionary Computation Conference (GECCO 2009), Montreal Canada. [Video1] [Video2]
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Auerbach, J., Bongard, J. C. (2009) How Robot Morphology and Training Order Affect the Learning of Multiple Behaviors. 2009 IEEE Congress on Evolutionary Computation (IEEE CEC 2009), Trondeim, Norway. [Video1] [Video2] [Video3] [Video4] [Video5]
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Bongard, J. (2008) Behavior Chaining: Incremental Behavior Integration for Evolutionary Robotics, Artificial Life XI, MIT Press, Cambridge, MA. [Source Code] [Video1] [Video2]
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Bongard, J. (2007) Synthesizing Physically-Realistic Environmental Models from Robot Exploration, Advances in Artificial Life: 9th European Conference, Springer-Verlag, Berlin, pp. 806-815.
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Bongard, J. (2007) Action-Selection and Crossover Strategies for Self-Modeling Machines, Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, ACM Press, New York, NY, pp. 198-205.
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Bongard, J. (2007) Exploiting Multiple Robots to Accelerate Self-Modeling, Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, ACM Press, New York, NY, pp. 214-221.
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Lipson, H., Bongard, J., Zykov, V., Malone, E. (2006) Evolutionary Robotics for Legged Machines: From Simulation to Physical Reality,Proceedings of the 9th Intl. Conference on Intelligent Autonomous Systems, University of Tokyo, Japan, 11-18.
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Bongard, J. C., Zykov, V. and H. Lipson (2006) Automated Synthesis of Body Schema using Multiple Sensor Modalities, in Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems (ALIFEX), pp. 220-226.
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Bongard J. and Lipson H. (2005) Reinventing the Wheel: Experiments in Evolutionary Geometry, Late Breaking Papers of the 2005 Genetic and Evolutionary Computation Conference, June 2005, Washington DC.
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Bongard J. and Lipson H. (2005c) `Managed Challenge' Alleviates Disengagement in Co-evolutionary System Identification, Proceedings of the 2005 Genetic and Evolutionary Computation Conference, June 2005, Washington DC, pp. 531-538.
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White P., Zykov V., Bongard J., and Lipson H. (2005) Three Dimensional Stochastic Reconfiguration of Modular Robots, Proceedings of Robotics: Science and Systems, MIT Press, Cambridge, MA, pp. 161-168.
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Zykov, V., J. Bongard and H. Lipson (2005) Co-evolutionary Variance Can Guide Physical Testing in Evolutionary System Identification,The 2005 NASA/DoD Conference on Evolvable Hardware, June 2005, Washington D.C., USA, pp. 213-220.
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Lipson, H. and J. Bongard (2004) An Exploration-Estimation Algorithm for Synthesis and Analysis of Engineering Systems Using Minimal Physical Testing, in Proceedings of the 2004 ASME Design Engineering Technical Conferences and Computer and Information in Engineering Conference, Salt Lake City, UT.
Zykov, V., Bongard, J. C. and H. Lipson (2004) Evolving Dynamics Gaits on a Physical Robot, in Late Breaking Papers for the 2004 Genetic and Evolutionary Computation Conference (GECCO), Seattle, WA.
Bongard, J. C. and H. Lipson (2004) Once More Unto the Breach: Co-evolving a Robot and its Simulator, in Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (ALIFE9), pp. 57-62.
Bongard, J. C. and H. Lipson (2004) Automated Robot Function Recovery after Unanticipated Failure or Environmental Change using a Minimum of Hardware Trials, in Proceedings of the NASA/DoD Conference on Evolvable Hardware, IEEE Computer Society, pp. 169-176.
Bongard, J. C. and H. Lipson (2004) Automating Genetic Network Inference with Minimal Physical Experimentation Using Coevolution, in Proceedings of the 2004 Genetic and Evolutionary Computation Conference (GECCO), Springer, pp. 333-345.
Bongard, J. C. and H. Lipson (2004) Automated Damage Diagnosis and Recovery for Remote Robotics, in Proceedings of the 2004 International Conference on Robotics and Automation (ICRA), Omnipress, pp. 3545-3550.
Bongard, J. C. (2002) Evolved Sensor Fusion and Dissociation in an Embodied Agent, in Proceedings of the EPSRC/BBSRC International Workshop Biologically-Inspired Robotics: The Legacy of W. Grey Walter, pp. 102-109.
Frutiger, D. R., J. C. Bongard and F. Iida (2002) Iterative Product Engineering: Evolutionary Robot Design, in Bidaud, P. and F. B. Amar (eds.), Proceedings of the Fifth International Conference on Climbing and Walking Robots, Professional Engineering Publishing, pp. 619-629.
Bongard, J. C. and R. Pfeifer (2002) A Method for Isolating Morphological Effects on Evolved Behaviour, in Hallam, B., Floreano, D. et al (eds.), Proceedings of the Seventh International Conference on the Simulation of Adaptive Behaviour (SAB2002), MIT Press, pp. 305-311.
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Bongard, J. C. and R. Pfeifer (2002) Relating Neural Network Performance to Morphological Differences in Embodied Agents, inProceedings of the Sixth International Conference on Cognitive and Neural Systems, Boston, USA.
Bongard, J. C. (2002) Evolving Modular Genetic Regulatory Networks, in Proceedings of the IEEE 2002 Congress on Evolutionary Computation (CEC2002), IEEE Press, pp. 1872-1877.
Paul, C. and J. C. Bongard (2001) The Road Less Travelled: Morphology in the Optimization of Biped Robot Locomotion, in Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2001), Hawaii, USA.
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Bongard, J. C. and C. Paul (2001) Making Evolution an Offer It Can't Refuse: Morphology and the Extradimensional Bypass, in J. Keleman and P. Sosik (eds.), Proceedings of the Sixth European Conference on Artificial Life, Prague, CZ, pp. 401-412. [Presentation available in PDF]
Bongard, J. C. and R. Pfeifer (2001) Repeated Structure and Dissociation of Genotypic and Phenotypic Complexity in Artificial Ontogeny, in Spector, L. et al (eds.), Proceedings of The Genetic and Evolutionary Computation Conference, GECCO-2001. San Francisco, CA: Morgan Kaufmann publishers, pp. 829-836.
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Bongard, J. C. and C. Paul (2000) Investigating Morphological Symmetry and Locomotive Efficiency using Virtual Embodied Evolution, in J.-A. Meyer et al (eds.), From Animals to Animats: The Sixth International Conference on the Simulation of Adaptive Behaviour, pp. 420-429
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Bongard, J. C. (2000) Reducing Collective Behavioural Complexity through Heterogeneity, in M. Bedau et al (eds.), Artificial Life VII:Proceedings of the Seventh International Conference, (MIT Press) , pp. 327-336 [Presentation available in PDF]
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Bongard, J. C. (2000) The Legion System: A Novel Approach to Evolving Heterogeneity for Collective Problem Solving, in R. Poli, W. Banzhaf et al (eds.), Genetic Programming: Third European Conference, pp. 25-37. (Springer-Verlag) [Presentation available in PDF]
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Bongard, J. C. (1999) Coevolutionary Dynamics of a Multi-Population Genetic Programming System, in Floreano, D., J.-D. Nicoud and F. Mondada (eds.), Proceedings of the Fifth European Conference on Artificial Life, pp. 316-321. (Springer-Verlag)
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A Larson, A Bernatskiy, C Cappelle, K Livingston, N Livingston, J Long, J Schwarz, M Smith & JC Bongard (2016). Recombination hotspots promote the evolvability of modular systems. Procs of the Genetic and Evolutionary Computation Conference (GECCO 2016). Poster.
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JC Bongard (2016) Evolving soft robots [editorial]. Soft Robotics 3(2) 43-44.
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A Bernatskiy & JC Bongard (2015) Exploiting the relationship between structural modularity and sparsity for faster network evolution. Genetic and Evolutionary Computation Conference (GECCO) Grad Student Workshop, Madrid, Spain.
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JC Bongard (2015) Manipulators and manipulanda. The Annual Edge Question: What Do You Think About Machines That Think?
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James P. Bagrow, Suma Desu, Morgan R. Frank, Narine Manukyan, Lewis Mitchell, Andrew Reagan, Eric E. Bloedorn, Lashon B. Booker, Luther K. Branting, Michael J. Smith, Brian F. Tivnan, Christopher M. Danforth, Peter S. Dodds, Joshua C. Bongard (2013) Shadow networks: Discovering hidden nodes with models of information flow. arXiv, 1312.6122
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Hornby, G. S., Bongard, J. C. (2013) Accelerating Interactive Evolutionary Algorithms through User Modeling. Workshop on Interactive Machine Learning at the 2013 International Conference on Intelligent User Interfaces.
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Celis, S., Bongard, J. C. (2012) Not All Physics Simulators Can Be Wrong in the Same Way. 2012 Genetic and Evolutionary Computation Conference (GECCO 2012), pp. 659-660, DOI: 10.1145/2330784.2330908.
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Beliveau, P., Hornby, G. S., Bongard, J. C. (2012) Interactive Simulated Robot Construction and Controller
Evolution. 2012 Genetic and Evolutionary Computation Conference (GECCO 2012), pp. 627-628, DOI: 10.1145/2330784.2330892.
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Bongard, J. C., Beliveau, P., Hornby, G. S. (2012) Avoiding Local Optima with Interactive Evolutionary Robotics. 2012 Genetic and Evolutionary Computation Conference (GECCO 2012), pp. 1405-1406, DOI: 10.1145/2330784.2330955.
Bongard, J. C. (2011) How Evolution Shapes the Way Roboticists Think. Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11), 7: 8-10.
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Bongard, J. (2011). Morphogenetic robotics recapitulates artificial ontogeny. Newsletter of the Autonomous Mental Development Technical Committee. 8(2): 3-4.
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Bongard, J. (2009). Biologically inspired computing. IEEE Computer, 42(4): 95-98.
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Bongard, J. C. (2009) A Riddle Wrapped In a Mystery. IEEE Newsletter of the Autonomous Mental Development Technical Committee, 6(2): 6.
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Lu, Z., Bongard, J. C. (2009) Exploiting Multiple Classifier Types with Active Learning 2009 Genetic and Evolutionary Computation Conference (GECCO 2009), Montreal Canada.
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Bongard, J. C. (2009) The Impact of Jointly Evolving Robot Morphology and Control on Adaptation Rate. 2009 Genetic and Evolutionary Computation Conference (GECCO 2009), Montreal Canada.
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Bongard, J. (2008). Probabilistic Robotics Book Review. Artificial Life, 14(2): 227-229.
Bongard, J. (2008) Embodied cognition: the other morphology. The Neuromorphic Engineer, DOI: 10.2417/1200812.1420.
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Lu, Z., Rughani, A. I., Tranmer, B. I., Bongard, J. (2008). Informative Sampling for Large Unbalanced Data Sets. 4th Workshop on Medical Applications of Genetic and Evolutionary Computation at GECCO 2008.
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Lungarella, M., Iida, F., Bongard, J. and Pfeifer, R. (2008) AI in the 21st century -- with historical reflections, Proceedings of the 50th Anniversary Summit of Artificial Intelligence, pp. 1-8.
Conduit, R., Adami, C., Lipson, H., Zykov, V. and Bongard, J. (2007). To sleep, perchance to dream. Science, 315: 1219-1220.