Publications
Copies of many of these publications are available upon request.
Books
Banzhaf, W., L. Spector, and L. Sheneman, editors. 2019. Genetic Programming Theory and Practice XVI. New York: Springer.
Spector, L. 2004/2007. Automatic Quantum Computer Programming: A Genetic Programming Approach. Boston, MA: Kluwer Academic Publishers. (Paperback edition published by Springer Science+Business Media, 2007). (Cover, ordering information and links)
Deb, K., R. Poli, W. Banzhaf, H-G Beyer, E. Burke, P. Darwen, D. Dasgupta, D. Floreano, J. Foster, M. Harman, O. Holland, P. Lanzi, L. Spector, A. Tettemanzi, D. Thierens and A. Tyrrell, editors. 2004. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2004. Lecture Notes in Computer Science, Vol. 3102-3103, Springer-Verlag.
Spector, L., E. Goodman, A. Wu, W.B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. Garzon, and E. Burke, editors. 2001. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2001. San Francisco, CA: Morgan Kaufmann Publishers. (Cover, description and ordering information)
Whitley, D., D. Goldberg, E. Cantu-Paz, L. Spector, I. Parmee, and H.-G. Beyer, editors. 2000. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2000. San Francisco, CA: Morgan Kaufmann Publishers.
Spector, L., U.-M. O’Reilly, W. Langdon, and P. Angeline, editors. 1999. Advances in Genetic Programming, Volume 3. Cambridge, MA: MIT Press. (MIT Press page, list of chapters and text from the Introduction)
Book Chapters
Spector, L. 2024. Ratcheted Random Search for Self-Programming Boolean Networks. In Genetic Programming Theory and Practice XXI. New York: Springer. To appear.
Spector, L., Ding, L., and Boldi, R. 2023. Particularity. In Genetic Programming Theory and Practice XX. New York: Springer. (preprint)
Saini, A. K., and Spector, L. 2021. Evolving and Analyzing modularity with GLEAM (Genetic Learning by Extraction and Absorption of Modules). In Genetic Programming Theory and Practice XVIII. New York: Springer. pp. 171-185.
Saini, A. K., and Spector, L. 2020. Using Modularity Metrics as Design Features to Guide Evolution in Genetic Programming. In Genetic Programming Theory and Practice XVII. New York: Springer. pp. 165-180.
Pantrdige, E., Helmuth, T., and Spector, L. 2020. Comparison of Linear Genome Representations For Software Synthesis. In Genetic Programming Theory and Practice XVII. New York: Springer. pp. 255-274. (pdf)
Metevier, B., A. K. Saini, and L. Spector. 2019. Lexicase Selection Beyond Genetic Programming. In Genetic Programming Theory and Practice XVI, edited by W. Banzhaf, L. Spector, and L. Sheneman. New York: Springer. (pdf)
Spector, L., W. La Cava, S. Shanabrook, T. Helmuth, and E. Pantridge. 2018. Relaxations of Lexicase Parent Selection. In Genetic Programming Theory and Practice XV, edited by W. Banzhaf, R. S. Olson, W. Tozier, and R. Riolo. New York: Springer, pp. 105-120. (pdf)
Helmuth, Thomas, Lee Spector, Nicholas Freitag McPhee, and Saul Shanabrook. 2017. Linear Genomes for Structured Programs. In Worzel, William, William Tozier, Brian W. Goldman, and Rick Riolo, Eds., Genetic Programming Theory and Practice XIV. New York: Springer. (pdf)
McPhee, N. F., M. D. Finzel, M. M. Casale, T. Helmuth and L. Spector. 2017. A detailed analysis of a PushGP run. In Worzel, William, William Tozier, Brian W. Goldman, and Rick Riolo, Eds., Genetic Programming Theory and Practice XIV. New York: Springer.
Helmuth, T., N. F. McPhee, and L. Spector. 2016. Lexicase selection for program synthesis: a diversity analysis. In Genetic Programming Theory and Practice XIII, edited by R. Riolo, W. Worzel, M. Kotanchek, and A. Kordon, pp. 151-167. New York: Springer. (pdf)
Kannappan, K., L. Spector, M. Sipper, T. Helmuth, W. La Cava, J. Wisdom, and O. Bernstein. 2015. Analyzing a decade of Human-competitive (“HUMIE”) winners – what can we learn? In Genetic Programming Theory and Practice XII, edited by R. Riolo, B. Worzel, and M. Kotanchek, pp. 149-156. New York: Springer. (pdf)
La Cava, W., and L. Spector. 2015. Inheritable Epigenetics in Genetic Programming. In Genetic Programming Theory and Practice XII, edited by R. Riolo, B. Worzel, and M. Kotanchek, pp. 37-51. New York: Springer.
Spector, L., and T. Helmuth. 2014. Uniform Linear Transformation with Repair and Alternation in Genetic Programming. In Genetic Programming Theory and Practice XI, edited by R. Riolo, J. H. Moore and M. Kotanchek, pp. 137-153. New York: Springer. (pdf)
Helmuth, T., and L. Spector. 2013. Evolving SQL Queries from Examples with Developmental Genetic Programming. In Genetic Programming Theory and Practice X, edited by R. L. Riolo, M. Ritchie, J. Moore, and E. Vladislavleva, pp. 1-14. New York: Springer. (pdf)
Spector, L., K. Harrington, B. Martin, and T. Helmuth. 2011. What’s in an Evolved Name? The Evolution of Modularity via Tag-Based Reference. In Genetic Programming Theory and Practice IX, edited by R. L. Riolo, E. Vladislavleva, and J. Moore, pp. 1-16. New York: Springer. (pdf)
Spector, L. 2010. Towards Practical Autoconstructive Evolution: Self-Evolution of Problem-Solving Genetic Programming Systems. In Genetic Programming Theory and Practice VIII, edited by R. L. Riolo, T. McConaghy, and E. Vladislavleva, pp. 17-33. New York: Springer. (pdf)
Langdon, W. B., R. I. McKay, and L. Spector. 2010. Genetic Programming. In Handbook of Metaheuristics, 2nd edition, edited by J.-Y. Potvin and M. Gendreau, pp. 185-226. New York: Springer-Verlag.
Coppinger, R., L. Spector, and L. Miller. 2010. What, if anything, is a Wolf? In The World of Wolves: New Perspectives on Ecology, Behaviour and Management, edited by M. Musiani, L. Boitani and P. Paquet. Calgary: The University of Calgary Press. (pdf)
Klein, J., and L. Spector. 2009. 3D Multi-Agent Simulations in the breve Simulation Environment. In Artificial Life Models in Software, 2nd edition, edited by A. Adamatzky and M. Komosinski, pp. 79-106. New York: Springer-Verlag.
Klein, J., and L. Spector. 2008. Genetic Programming with Historically Assessed Hardness. In Genetic Programming Theory and Practice VI, edited by R. L. Riolo, T. Soule, and B. Worzel, pp. 61-74. New York: Springer-Verlag. (pdf)
Spector, L., and J. Klein. 2006. Multidimensional Tags, Cooperative Populations, and Genetic Programming. In Genetic Programming Theory and Practice IV, edited by R.L. Riolo, T. Soule, and B. Worzel, pp. 97-112. New York: Springer-Verlag. (pdf)
Spector, L., and J. Klein. 2005. Trivial Geography in Genetic Programming. In Genetic Programming Theory and Practice III, edited by T. Yu, R.L. Riolo, and B. Worzel, pp. 109-124. Boston, MA: Kluwer Academic Publishers. (pdf)
Grafman, J., L. Spector, and M.J. Rattermann. 2005. Planning and the Brain. In The Cognitive Psychology of Planning, edited by R. Morris and G. Ward, pp. 181-198. New York, NY: Psychology Press (Taylor & Francis Group).
Spector, L. 2003. An Essay Concerning Human Understanding of Genetic Programming. In Genetic Programming: Theory and Practice, edited by R.L Riolo and W. Worzel, pp. 11-24. Boston, MA: Kluwer Academic Publishers. (pdf)
Spector, L., H. Barnum, and H.J. Bernstein. 1999. Quantum Computing Applications of Genetic Programming. In Advances in Genetic Programming, Volume 3, edited by L. Spector, U.-M. O’Reilly, W. Langdon, and P. Angeline, pp. 135-160. Cambridge, MA: MIT Press. (pdf)
Spector, L. 1996. Simultaneous Evolution of Programs and their Control Structures. In Advances in Genetic Programming 2, edited by P. Angeline and K. Kinnear, pp. 137-154. Cambridge, MA: MIT Press. (postscript, pdf)
Spector, L. and J. Grafman. 1994. Planning, Neuropsychology, and Artificial Intelligence: Cross-Fertilization. In Handbook of Neuropsychology, Volume 9, edited by F. Boller, and J. Grafman, 377-392. Amsterdam: Elsevier Science Publishers B.V.
Journal Publications
Boldi, R., M. Briesch, D. Sobania, A. Lalejini, T. Helmuth, F. Rothlauf, C. Ofria, and L. Spector. 2024. Informed Down-Sampled Lexicase Selection: Identifying Productive Training Cases for Efficient Problem Solving. In Evolutionary Computation, doi: https://doi.org/10.1162/evco_a_00346
Ding, L., and L. Spector. 2023. Multi-Objective Evolutionary Architecture Search for Parameterized Quantum Circuits. In Entropy, Vol 25, No. 1: 93. (full text)
Spector, L. 2022. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 23, No. 1, pp. 1-2.
Helmuth, T., and L. Spector. 2021. Problem-solving benefits of down-sampled lexicase selection. In Artificial Life, Vol 27, Issue 3-4, pp. 183–203. (pdf)
Spector, L. 2021. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 22, No. 1, pp. 1-2.
Helmuth, T., Pantridge, E., and L. Spector. 2020. On the importance of specialists for lexicase selection. In Genetic Programming and Evolvable Machines, Vol. 21, pp. 349–373. https://doi.org/10.1007/s10710-020-09377-2. (full text)
Spector, L. 2020. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 21, No. 1, pp. 1-2.
O’Neill, M., and Lee Spector. 2020. Automatic programming: The open issue? Genetic Programming and Evolvable Machines, Vol. 21, pp. 251-262. https://doi.org/10.1007/s10710-019-09364-2 (full text)
Spector, L. 2019. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 20, No. 1, pp. 1-2.
La Cava, W., S. Silva, K. Danai, L. Spector, L. Vanneschi, and J. H. Moore. 2019. Multidimensional genetic programming for multiclass classification. In Swarm and Evolutionary Computation, Vol. 44, pp. 260-272. https://doi.org/10.1016/j.swevo.2018.03.015
La Cava, W., T. Helmuth, L. Spector, and J. H. Moore. 2018. A Probabilistic and Multi-Objective Analysis of Lexicase Selection and ε-Lexicase Selection. In Evolutionary Computation, Vol. 27, Issue 3, pp. 377-402. https://doi.org/10.1162/evco_a_00224 (pdf)
Clark, D. M., and L. Spector. 2018. Evolution of algebraic terms 3: Term continuity and beam algorithms. In International Journal of Algebra and Computation, Vol. 28, No. 05, pp. 759-790. https://doi.org/10.1142/S0218196718500352.
Spector, L. 2018. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 19, No. 1-2, pp. 1-2.
Spector, L. 2017. Introduction to the peer commentary special section on “On the Mapping of Genotype to Phenotype in Evolutionary Algorithms” by Peter A. Whigham, Grant Dick, and James Maclaurin. In Genetic Programming and Evolvable Machines, Vol. 18, No. 3, pp. 351-352. DOI: 10.1007/s10710-017-9287-y (full text)
McCaffrey, T., and L. Spector. 2017. An approach to human-machine collaboration in innovation. In AI-EDAM: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, DOI: https://doi.org/10.1017/S0890060416000524
DelRosso, N. V., S. Hews, L. Spector, and N. D. Derr. 2017. A Molecular Circuit Regenerator to Implement Iterative Strand Displacement Operations. In Angewandte Chemie International Edition, DOI: https://doi.org/10.1002/anie.201610890.
Spector, L. 2017. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 18, No. 1, pp. 1-2. (full text)
Taylor, T., M. Bedau, A. Channon, D. Ackley, W. Banzhaf, G. Beslon, E. Dolson, T. Froese, S. Hickinbotham, T. Ikegami, B. McMullin, N. Packard, S. Rasmussen, N. Virgo, E. Agmon, E. Clark, S. McGregor, C. Ofria, G. Ropella, L. Spector, K. O. Stanley, A. Stanton, C. Timperley, A. Vostinar, and M. Wiser. 2016. Open-Ended Evolution: Perspectives from the OEE Workshop in York. In Artificial Life, Vol. 22, No. 3, pp. 408-423. (pdf)
La Cava, W., K. Danai, and L. Spector. 2016. Inference of compact nonlinear dynamic models by epigenetic local search. In Engineering Applications of Artificial Intelligence, Vol. 55, pp. 292-306. (pdf)
La Cava, W., K. Danai, L. Spector, P. Fleming, A. Wright, and M. Lackner. 2016. Automatic identification of wind turbine models using evolutionary multiobjective optimization. In Renewable Energy, Volume 87, Part 2, pp. 892-902.
Clark, D. M., M. Keijzer, and L. Spector. 2016. Evolution of algebraic terms 2: Deep drilling algorithm. In International Journal of Algebra and Computation, Vol. 26, No. 6, pp. 1141-1176.
Banzhaf, W., B. Baumgaertner, G. Beslon, R. Doursat, J. A. Foster, B. McMullin, V. Veloso de Melo, T. Miconi, L. Spector, S. Stepney, and R. White. 2016. Defining and simulating open-ended novelty: requirements, guidelines, and challenges. In Theory in Biosciences, pp. 1-31.
Spector, L. 2016. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 17, No. 1, pp. 1-2.
Spector, L. 2015. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 16, No. 1, pp. 1-2.
Helmuth, T., L. Spector, and J. Matheson. 2014. Solving Uncompromising Problems with Lexicase Selection. In IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2014.2362729. (pdf)
Escobedo, R., C. Muro, L. Spector, and R. P. Coppinger. 2014. Group size, individual role differentiation and effectiveness of cooperation in a homogeneous group of hunters. In Journal of the Royal Society Interface, Vol. 11, No. 95, 20140204, pp. 1-10. (Full text on-line)
Spector, L. 2014. Peer commentary on Wolfgang Banzhaf’s “Genetic Programming and Emergence.” In Genetic Programming and Evolvable Machines, Vol. 15, No. 1, pp. 61-62.
Spector, L. 2014. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 15, No. 1, pp. 1-2.
Spector, L. 2013. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 14, No. 1, pp. 1-2.
McCaffrey, T., and L. Spector. 2012. Behind every innovative solution lies an obscure feature. In Knowledge Management & E-Learning: An International Journal, Vol. 4, No. 2, pp. 146-156. (Full text on-line)
Spector, L. 2012. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 13, No. 1, pp. 1-2.
Muro, C., R. Escobedo, L. Spector, and R. P. Coppinger. 2011. Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations. In Behavioural Processes, Vol. 88, pp. 192-197.
Muro, C., R. Escobedo, R. P. Coppinger, and L. Spector. 2011. Wolf-pack hunting strategy: an emergent collective behavior described by a classical robotic model (abstract). In Journal of Veterinary Behavior: Clinical Applications and Research, Vol. 6, No. 1, p. 94.
Spector, L. 2011. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 12, No. 1, pp. 1-2.
Niekum, S., A. Barto, and L. Spector. 2010. Genetic Programming for Reward Function Search. In IEEE Transactions on Autonomous Mental Development, Vol. 2, No. 2, pp. 83-90. (pdf)
Spector, L. 2010. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 11, No. 1, pp. 1-2.
Spector, L. 2009. Editorial Introduction. In Genetic Programming and Evolvable Machines, Vol. 10, No. 1, pp. 1-2.
Spector, L. 2008. Introduction to the Special Issue on Genetic Programming for Human-Competitive Designs. In AI-EDAM: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 22, No. 3, pp. 183-184. (pdf)
Spector, L., and J. Klein. 2008. Machine Invention of Quantum Computing Circuits by Means of Genetic Programming. In AI-EDAM: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 22, No. 3, pp. 275-283. (pdf)
Spector, L. 2006. Evolution of Artificial Intelligence. In Artificial Intelligence, Vol. 170, Issue 18, pp. 1251-1253. (pdf)
Spector, L., and J. Klein. 2006. Genetic Stability and Territorial Structure Facilitate the Evolution of Tag-mediated Altruism. In Artificial Life, Vol. 12, No. 4, pp. 553-560. (pdf)
Spector, L., J. Klein, and K. Harrington. 2005. Selection Songs: Evolutionary Music Computation. In YLEM Journal, Vol. 25, No. 6 & 8, pp. 24-26 (associated web page, including link to full text).
Spector, L., J. Klein, C. Perry, and M. Feinstein. 2005. Emergence of Collective Behavior in Evolving Populations of Flying Agents. In Genetic Programming and Evolvable Machines, Vol. 6, No. 1, pp. 111-125. (pdf)
Spector, L. 2002. Book Review: The Quest for the Quantum Computer, by J. Brown. In Genetic Programming and Evolvable Machines, Vol. 3, No. 4, pp. 391-393.
Spector, L., and A. Robinson. 2002. Genetic Programming and Autoconstructive Evolution with the Push Programming Language. In Genetic Programming and Evolvable Machines, Vol. 3, No. 1, pp. 7-40. (Full text, pdf)
Spector, L. 2002. Hierarchy Helps it Work That Way. In Philosophical Psychology, Vol. 15, No. 2 (June, 2002), pp. 109-117. (pdf)
Rattermann, M.J., L. Spector, J. Grafman, H. Levin, and H. Harward. 2001. Partial and total-order planning: evidence from normal and prefrontally damaged populations. In Cognitive Science, Vol. 25, No. 6 (November/December, 2001), pp. 941-975. (pdf)
Barnum, H., H.J. Bernstein, and L. Spector. 2000. Quantum circuits for OR and AND of ORs. Journal of Physics A: Mathematical and General, Vol. 33 No. 45 (17 November 2000), pp. 8047-8057. (postscript, pdf)
Spector, L. 2000. The Evolution of Arbitrary Computational Processes. In IEEE Intelligent Systems, May/June 2000, pp. 80-83. (Entire special section in final form, pdf; Preprint version of just this article: postscript, pdf).
Spector, L. 1997. Automatic Generation of Intelligent Agent Programs. In IEEE Expert. Jan-Feb 1997, pp. 3-4. (pdf)
Spector, L. 1996. Social Structure in Evolutionary Computation Systems. In Communication and Cognition-Artificial Intelligence. Vol. 13, nos 2-3. pp. 141-161.
Spector, L. 1995. Artificial Intelligence as the Liberal Arts of Computer Science. In SIGART Bulletin: Special Issue on AI Education. Volume 6, Number 2, pp. 8-10. The Association for Computing Machinery. (pdf)
Evett, M. P., J. A. Hendler, and L. Spector. 1994. Parallel Knowledge Representation on the Connection Machine. Journal for Parallel and Distributed Computing. Volume 22, number 2, pp. 168-184.
Grafman, J., A. Sirigu, L. Spector, and J. Hendler. 1993. Damage to the prefrontal cortex leads to decomposition of structured event complexes. In The Journal of Head Trauma Rehabilitation, Volume 8, Number 1, Aspen Publishers, Inc., pp. 73-87.
Spector, L. and J. Hendler. 1992. Planning and Reacting Across Supervenient Levels of Representation. In International Journal of Intelligent and Cooperative Information Systems, Volume 1, Numbers 3 & 4, pp. 411-449.
Spector, L. and J. Hendler. 1989. Book Review: Minimal Rationality, by C. Cherniak. In Artificial Intelligence, Volume 39, Number 1.
Conference and Workshop Papers
Ni, A., and L. Spector. 2024. Effective Adaptive Mutation Rates for Program Synthesis. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘24). Association for Computing Machinery, New York, NY, USA.
Helmuth, T., J. Fedoroff, E. Pantridge, and L. Spector. 2024. Facilitating Function Application in Code Building Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘24). Association for Computing Machinery, New York, NY, USA.
Boldi, R., A. Bao, M. Briesch, T. Helmuth, D. Sobania, L. Spector, and A. Lalejini. 2024. Untangling the Effects of Down-Sampling and Selection in Genetic Programming. In Artificial Life Conference Proceedings, ALIFE-2024.
Ding, L., J. Zhang, J. Clune, L. Spector, and J. Lehman. 2024. Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization. In Proceedings of The Forty-first International Conference on Machine Learning, ICML-2024.
Ni, A., Ding, L., and Spector, L. 2024. DALex: Lexicase-Like Selection via Diverse Aggregation. In Proceedings of EuroGP 2024. Lecture Notes in Computer Science, vol 14631. Springer, Cham. (pdf)
Helmuth, T., Pantridge, E., Frazier, J.G., and Spector, L. 2024. Generational Computation Reduction in Informal Counterexample-Driven Genetic Programming. In Proceedings of EuroGP 2024. Lecture Notes in Computer Science, vol 14631. Springer, Cham. (pdf)
Ding, L., E. Pantridge, and L. Spector. 2023. Probabilistic Lexicase Selection. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘23). Association for Computing Machinery, New York, NY, USA, 1073–1081. (pdf; preprint pdf)
Boldi, R., and L. Spector. 2023. Can the Problem-Solving Benefits of Quality Diversity be Obtained Without Explicit Diversity Maintenance? In Genetic and Evolutionary Computation Conference Companion (GECCO-2023 Companion). Association for Computing Machinery, New York, NY, USA, 2152–2156. (pdf)
Boldi, R., T. Helmuth, and L. Spector. 2022. The environmental discontinuity hypothesis for down-sampled lexicase selection. In the Why it didn’t work-shop at ALIFE 2022: The 2022 Conference on Artificial Life. (pdf)
Pantridge, E., T. Helmuth, and L. Spector. 2022. Functional code building genetic programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘22), pp. 1000-1008. Published by the Association for Computing Machinery. (pdf)
Ding, L., and L. Spector. 2022. Evolutionary quantum architecture search for parametrized quantum circuits. In GECCO ‘22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 2190-2195. Published by the Association for Computing Machinery. (pdf)
Ding, L., R. Boldi, T. Helmuth, and L. Spector. 2022. Lexicase selection at scale. In GECCO ‘22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 2054-2062. Published by the Association for Computing Machinery. (pdf)
Ding, L., and L. Spector. 2022. Optimizing Neural Networks with Gradient Lexicase Selection. In The Tenth International Conference on Learning Representations (ICLR 2022). Published at openreview.net: pdf
Ding, L., and L. Spector. 2021. Evolving neural selection with adaptive regularization. In Proceedings of GECCO 2021 Companion, pp. 1717-1725. Genetic and Evolutionary Computation Conference (GECCO ‘21). Published by the Association for Computing Machinery. (pdf)
Helmuth, T., E. Pantridge, G. Woolson, and L. Spector. 2020. Genetic Source Sensitivity and Transfer Learning in Genetic Programming. In Artificial Life Conference Proceedings, pp. 303-311. MIT Press. (pdf)
Helmuth, T., and Spector, L. 2020. Explaining and Exploiting the Advantages of Down-sampled Lexicase Selection. In Artificial Life Conference Proceedings, pp. 341-349. MIT Press. (pdf)
Pantridge, E., and L. Spector. 2020. Code Building Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘20), pp. 994-1002. Published by the Association for Computing Machinery.
Saini, A. K., and L. Spector. 2020. Effect of Parent Selection Methods on Modularity. In EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming, pp. 184-194. Springer Verlag.
Winner, Best Paper Award
Aenugu, S., and Spector, L. 2019. Lexicase selection in learning classifier systems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘19), pp. 356-364. Published by the Association for Computing Machinery.
Helmuth, T., Pantridge, E., and Spector, L. 2019. Lexicase selection of specialists. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘19), pp. 1030-1038. Published by the Association for Computing Machinery.
Winner, Best Paper Award, Genetic Programming Track
Saini, A. K., and Spector, L. 2019. Modularity metrics for genetic programming. In Proceedings of GECCO ’19 Companion, pp. 2056-2059. Genetic and Evolutionary Computation Conference (GECCO ‘19). Published by the Association for Computing Machinery.
Helmuth, T., N. F. McPhee, and L. Spector. 2018. Program Synthesis using Uniform Mutation by Addition and Deletion. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘18). Published by the Association for Computing Machinery.
Winner, Best Paper Award, Genetic Programming Track
La Cava, W., S. Silva, K. Danai, L. Vanneschi, J. H. Moore, and L. Spector. 2018. A multidimensional genetic programming approach for identifying epistatic gene interactions. In Proceedings of GECCO ’18 Companion. Genetic and Evolutionary Computation Conference, Kyoto, Japan. Published by the Association for Computing Machinery.
Pantridge, E. R., T. Helmuth, N. F. McPhee, and L. Spector. 2018. Specialization and Elitism in Lexicase and Tournament Selection. In Proceedings of GECCO ’18 Companion. Genetic and Evolutionary Computation Conference, Kyoto, Japan. Published by the Association for Computing Machinery.
Pantridge, E. R., and L. Spector. 2018. Plushi: An Embeddable, Language Agnostic, Push Interpreter. In Proceedings of GECCO ’18 Companion. Genetic and Evolutionary Computation Conference, Kyoto, Japan. Published by the Association for Computing Machinery.
Helmuth, T., N. F. McPhee, E. Pantridge and L. Spector. 2017. Improving generalization of evolved programs through automatic simplification. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘17). ACM, New York, NY, USA, 937-944. DOI: https://doi.org/10.1145/3071178.3071330 (pdf)
Nominated, Best Paper Award, Genetic Programming Track
Pantridge, E., T. Helmuth, N. F. McPhee, L. Spector. 2017. On the Difficulty of Benchmarking Inductive Program Synthesis Methods. In Proceedings of GECCO ’17 Companion, Berlin, Germany. DOI: http://dx.doi.org/10.1145/3067695.3082533. (pdf)
Spector, L. and E. Moscovici. 2017. Recent Developments in Autoconstructive Evolution. Extended abstract for invited presentation. In Proceedings of GECCO ’17 Companion, Berlin, Germany. DOI: http://dx.doi.org/10.1145/3067695.3082058. (pdf)
Pantridge, E. and L. Spector. 2017. PyshGP: PushGP in Python. In Proceedings of GECCO ’17 Companion, Berlin, Germany. DOI: http://dx.doi.org/10.1145/3067695.3082468. (pdf)
La Cava, W., S. Silva, L. Vanneschi, L. Spector, and J. Moore. 2017. Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. In Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science, Vol. 10199. Springer.
Helmuth, T., N. F. McPhee, and L. Spector. 2016. The Impact of Hyperselection on Lexicase Selection. In Proceedings of the 2016 Genetic and Evolutionary Computation Conference, GECCO’16. ACM Press. pp. 717-724. Nominated, Best Paper Award, Genetic Programming Track. (pdf)
Nominated, Best Paper Award, Genetic Programming Track
La Cava, W., L. Spector, and K. Danai. 2016. Epsilon-lexicase Selection for Regression. In Proceedings of the 2016 Genetic and Evolutionary Computation Conference, GECCO’16. ACM Press. pp. 741-748. (pdf as published, post-publication revision pdf)
Pantridge, E., and L. Spector. 2016. Evolution of Layer Based Neural Networks: Preliminary Report. In Companion Publication of the 2016 Genetic and Evolutionary Computation Conference, GECCO’16 Companion. ACM Press. pp. 1015-1022. (pdf)
Helmuth, T., N. F. McPhee, and L. Spector. 2016. Effects of Lexicase and Tournament Selection on Diversity Recovery and Maintenance. In Companion Publication of the 2016 Genetic and Evolutionary Computation Conference, GECCO’16 Companion. ACM Press. pp. 993-990. (pdf)
Spector, L., N. F. McPhee, T. Helmuth, M. M. Casale, and J. Oks. 2016. Evolution Evolves with Autoconstruction. In Companion Publication of the 2016 Genetic and Evolutionary Computation Conference, GECCO’16 Companion. ACM Press. pp. 1349-1356. (pdf)
McPhee, N. F., M. M. Casale, M. Finzel, T. Helmuth, and L. Spector. 2016. Visualizing Genetic Programming Ancestries. In Companion Publication of the 2016 Genetic and Evolutionary Computation Conference, GECCO’16 Companion. ACM Press. pp. 1419-1426. (pdf)
Spector, L.. Work in Progress on Autoconstructive Evolution (Extended Abstract). 2016. In Proceedings of the 6th International Conference on Metaheuristics and nature inspired computing, META’2016. Marrakech, Morocco.
La Cava, W., K. Danai, L. Spector, P. Fleming, M. A. Lackner, and A. Wright. 2015 Automatic Identification of Closed-loop Wind Turbine Dynamics via Genetic Programming. In Proceedings of the ASME 2015 Dynamic Systems and Control Conference.
La Cava, W., T. Helmuth, L. Spector, and K. Danai. 2015. Genetic Programming with Epigenetic Local Search. In Proceedings of the 2015 Genetic and Evolutionary Computation Conference, GECCO’15. ACM Press. 1055-1062. Nominated, Best Paper Award, Genetic Programming Track. (pdf)
Helmuth, T., and L. Spector. 2015. General Program Synthesis Benchmark Suite. In Proceedings of the 2015 Genetic and Evolutionary Computation Conference, GECCO’15. ACM Press. pp. 1039-1046. (pdf)
Liskowski, P., K. Krawiec, T. Helmuth, and L. Spector. 2015. Comparison of Semantic-aware Selection Methods in Genetic Programming. In Companion Publication of the 2015 Genetic and Evolutionary Computation Conference, GECCO’15 Companion. ACM Press. pp. 1301-1307. (pdf)
Helmuth, T., and L. Spector. 2014. Word Count as a Traditional Programming Benchmark Problem for Genetic Programming. In Proceedings of the 2014 Genetic and Evolutionary Computation Conference, GECCO’14. ACM Press. pp. 919-926. (pdf)
Trujillo, L., L. Spector, E. Naredo, and Y. Martinez. 2013. A behavior-based analysis of modal problems. In Companion Publication of the 2013 Genetic and Evolutionary Computation Conference, GECCO’13 Companion. ACM Press. pp. 1047-1054.
Helmuth, T., and L. Spector. 2013. Evolving a digital multiplier with the PushGP genetic programming system. In Companion Publication of the 2013 Genetic and Evolutionary Computation Conference, GECCO’13 Companion. ACM Press. pp. 1627-1634. 
(Free Access) (With Erratum Notice)
Spector, L., K. Harrington, and T. Helmuth. 2012. Tag-based Modularity in Tree-based Genetic Programming. In Proceedings of the 2012 Genetic and Evolutionary Computation Conference, GECCO’12. ACM Press. pp. 815-822. (pdf)
Spector, L. 2012. Assessment of Problem Modality by Differential Performance of Lexicase Selection in Genetic Programming: A Preliminary Report. In Companion Publication of the 2012 Genetic and Evolutionary Computation Conference, GECCO’12 Companion. ACM Press. pp. 401-408. (pdf)
Tosch, E., and L. Spector. 2012. Achieving COSMOS: A Metric for Determining When to Give up and When to Reach for the Stars. In Companion Publication of the 2012 Genetic and Evolutionary Computation Conference, GECCO’12 Companion. ACM Press. pp. 417-424. (pdf)
Harrington, K. I., L. Spector, J. B. Pollack, and U.-M. O’Reilly. 2012. Autoconstructive Evolution for Structural Problems. In Companion Publication of the 2012 Genetic and Evolutionary Computation Conference, GECCO’12 Companion. ACM Press. pp. 75-82. (pdf)
Spector, L., B. Martin, K. Harrington, and T. Helmuth. 2011. Tag-Based Modules in Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2011). ACM Press. pp. 1419-1426. (pdf, associated web page)
Helmuth, T., L. Spector, and B. Martin. 2011. Size-Based Tournaments for Node Selection. In GECCO’11 Workshops, Genetic and Evolutionary Computation Conference. ACM Press. pp. 799-802. (pdf, Erratum Note)
Harrington, K., E. Tosch, L. Spector, and J. Pollack. 2011. Compositional Autoconstructive Dynamics. Unifying Themes in Complex Systems Volume VIII: Proceedings of the Eighth International Conference on Complex Systems. New England Complex Systems Institute Series on Complexity. NECSI Knowledge Press. pp. 856-870. http://necsi.edu/events/iccs2011/proceedings.html. (pdf)
McCaffrey, A.J. and L. Spector. 2011. How the Obscure Features Hypothesis leads to Innovation Assistant software. In Proceedings of the Second International Conference on Computational Creativity, pp. 120-122. Universidad Autonoma Metropolitana, Mexico. (pdf)
Spector, L., D. M. Clark, I. Lindsay, B. Barr, and J. Klein. 2008. Genetic Programming for Finite Algebras. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2008). ACM Press. (associated web page, including link to full text and code)
Spector, L., J. Klein, and M. Feinstein. 2007. Division blocks and the open-ended evolution of development, form, and behavior. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2007), pp. 316-323. ACM Press. (associated web page, including link to full text, movie, and code)
Klein, J., and L. Spector. 2007. Unwitting Distributed Genetic Programming via Asynchronous JavaScript and XML. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2007), pp. 1628-1635. ACM Press. (associated web page, including link to full text)
Spector, L., J. Klein, and M. Keijzer. 2005. The Push3 Execution Stack and the Evolution of Control. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005), pp. 1689-1696. Springer-Verlag. (pdf)
Stout, A., and L. Spector. 2005. Validation of Evolutionary Activity Metrics for Long-Term Evolutionary Dynamics. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005), pp. 137-142. Springer-Verlag. (pdf)
Spector, L., J. Klein, K. Harrington, and R. Coppinger. 2005. Teaching the Evolution of Behavior with SuperDuperWalker. In Proceedings of the 12th International Conference on Artificial Intelligence in Education (AIED-2005), pp. 923-925. IOS Press. (pdf)
Spector, L., J. Klein, and C. Perry. 2004. Tags and the Evolution of Cooperation in Complex Environments. In Proceedings of the AAAI 2004 Symposium on Artificial Multiagent Learning. Melno Park, CA: AAAI Press. (pdf)
Spector, L., J. Klein, C. Perry, and M. Feinstein. 2003. Emergence of Collective Behavior in Evolving Populations of Flying Agents. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003). Springer-Verlag. pp. 61-73. Winner, Best Paper Award (AAAA Track). (associated web page, including link to full text)
Spector, L., and H.J. Bernstein. 2003. Communication Capacities of Some Quantum Gates, Discovered in Part through Genetic Programming. In J.H. Shapiro and O. Hirota, Eds., Proceedings of the Sixth International Conference on Quantum Communication, Measurement, and Computing (QCMC), pp. 500-503. Princeton, NJ: Rinton Press. (prepress version with additional figures: pdf)
Spector, L. 2002. Adaptive populations of endogenously diversifying Pushpop organisms are reliably diverse. In R. K. Standish, M. A. Bedau, and H. A. Abbass (eds.), Proceedings of Artificial Life VIII, the 8th International Conference on the Simulation and Synthesis of Living Systems, pp. 142-145. Cambridge, MA: The MIT Press. (pdf)
Spector, L., and J. Klein. 2002. Evolutionary Dynamics Discovered via Visualization in the BREVE Simulation Environment. In Bilotta et al. (eds), Workshop Proceedings of the 8th International Conference on the Simulation and Synthesis of Living Systems, pp. 163-170. Sydney, Australia: University of New South Wales. (associated web page, including link to full text)
Spector, L., and J. Klein. 2002. Complex Adaptive Music Systems in the BREVE Simulation Environment. In Bilotta et al. (eds), Workshop Proceedings of the 8th International Conference on the Simulation and Synthesis of Living Systems, pp. 17-23. Sydney, Australia: University of New South Wales. (associated web page, including link to full text)
Spector, L., and A. Robinson. 2002. Multi-type, Self-adaptive Genetic Programming as an Agent Creation Tool. In Proceedings of the Workshop on Evolutionary Computation for Multi-Agent Systems, ECOMAS-2002, International Society for Genetic and Evolutionary Computation. (pdf)
Crawford-Marks, R., and L. Spector. 2002. Size Control via Size Fair Genetic Operators in the PushGP Genetic Programming System. In W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, and N. Jonoska (editors), Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2002, pp. 733-739. San Francisco, CA: Morgan Kaufmann Publishers. (pdf)
Spector, L. 2001. Autoconstructive Evolution: Push, PushGP, and Pushpop. In Spector, L., E. Goodman, A. Wu, W.B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. Garzon, and E. Burke, editors, Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2001, pp. 137-146. San Francisco, CA: Morgan Kaufmann Publishers. (pdf)
Weisler, S., R. Bellin, L. Spector, and N. Stillings. 2001. An Inquiry-based Approach to E-learning: The CHAT Digital Learning Environment. In Proceedings of SSGRR-2001, the International Conference on Advances in Infrastructure for Electronic Business, Science, and Education on the Internet. Scuola Superiore G. Reiss Romoli, L’Aquila, Italy. Proceedings ISBN: ISBN:88-85280-61-7, URL: http://www.ssgrr.it/en/ssgrr2001/papers.htm. (pdf)
Spector, L., H. Barnum, and H.J. Bernstein. 1998. Genetic Programming for Quantum Computers. In Genetic Programming 1998: Proceedings of the Third Annual Conference, edited by J.R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D.B. Fogel, M.H. Garzon, D.E. Goldberg, H. Iba, and R.L. Riolo. pp. 365-374. San Francisco, CA: Morgan Kaufmann. (pdf)
Luke, S., and L. Spector. 1998. A Revised Comparison of Crossover and Mutation in Genetic Programming. In Genetic Programming 1998: Proceedings of the Third Annual Conference, edited by J.R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D.B. Fogel, M.H. Garzon, D.E. Goldberg, H. Iba, and R.L. Riolo. pp. 208-214. San Francisco, CA: Morgan Kaufmann. (pdf)
Luke, S. and L. Spector. 1997. A Comparison of Crossover and Mutation in Genetic Programming. In Genetic Programming 1997: Proceedings of the Second Annual Conference, 240-248. Cambridge, MA: The MIT Press. (pdf)
Luke, S., L. Spector, D. Rager, and J. Hendler. 1997. Ontology-based Web Agents. In Proceedings of the First International Conference on Autonomous Agents, 59-66. W. L. Johnson, Editor. New York: ACM Press. (pdf)
Spector, L. 1997. Genetic Programming of Cognitive Models. In M.G. Shafto and P. Langley (editors), Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society, p. 1059. Mahwah, NJ: Lawrence Erlbaum Associates, Publishers.
Spector, L., and K. Stoffel. 1996. Automatic Generation of Adaptive Programs. In P. Maes, M. Mataric, J.-A. Meyer, J. Pollack, and S.W. Wilson (editors), From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, 476-483. Cambridge, MA: The MIT Press. (postscript; pdf)
Spector, L., and S. Luke. 1996. Culture Enhances the Evolvability of Cognition. In G. Cottrell (editor), Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society, 672-677. Mahwah, NJ: Lawrence Erlbaum Associates, Publishers. (postscript, pdf)
Spector, L., and S. Luke. 1996. Cultural Transmission of Information in Genetic Programming. In Koza, John R., Goldberg, David E., Fogel, David B., and Riolo, Rick L. (editors) Genetic Programming 1996: Proceedings of the First Annual Conference, 209-214. Cambridge, MA: The MIT Press. (postscript, pdf)
Spector, L., and K. Stoffel. 1996. Ontogenetic Programming. In Koza, John R., Goldberg, David E., Fogel, David B., and Riolo, Rick L. (editors) Genetic Programming 1996: Proceedings of the First Annual Conference, 394-399. Cambridge, MA: The MIT Press. (postscript, pdf)
Luke, S., and L. Spector. 1996. Evolving Teamwork and Coordination with Genetic Programming. In Koza, John R., Goldberg, David E., Fogel, David B., and Riolo, Rick L. (editors) Genetic Programming 1996: Proceedings of the First Annual Conference, 150-156. Cambridge, MA: The MIT Press. (postscript, pdf)
Stoffel, K., and L. Spector. 1996. High-Performance, Parallel, Stack-Based Genetic Programming. In Koza, John R., Goldberg, David E., Fogel, David B., and Riolo, Rick L. (editors) Genetic Programming 1996: Proceedings of the First Annual Conference, 224-229. Cambridge, MA: The MIT Press. (postscript, pdf)
Spector, L., and A. Alpern. 1994. Criticism, Culture, and the Automatic Generation of Artworks. In Proceedings of the Twelfth National Conference on Artificial Intelligence, AAAI-94, 3-8. Menlo Park, CA and Cambridge, MA: AAAI Press/The MIT Press. (pdf)
Spector, L. 1994. Genetic Programming and AI Planning Systems. In Proceedings of the Twelfth National Conference on Artificial Intelligence, AAAI-94, 1329-1334. Menlo Park, CA and Cambridge, MA: AAAI Press/The MIT Press. (pdf)
Spector, L., M. J. Rattermann, and K. Prentice. 1994. Ordering Relations in Human and Machine Planning. In Proceedings of the Twelfth National Conference on Artificial Intelligence, AAAI-94, 80-85. Menlo Park, CA and Cambridge, MA: AAAI Press/The MIT Press.
Spector, L., and J. Hendler. 1994. The Use of Supervenience in Dynamic-World Planning. In Proceedings of the Second International Conference on Artificial Intelligence Planning Systems, edited by Kristian Hammond, 158-163. Menlo Park, CA: AAAI Press.
Spector, L. and J. Hendler. 1990. An Abstraction-Partitioned Model for Reactive Planning. In Proceedings of the Fifth Rocky Mountain Conference on Artificial Intelligence (RMCAI-90), New Mexico State University, Las Cruces, New Mexico.
Evett, M., L. Spector, and J. Hendler. 1989. Knowledge Representation on the Connection Machine. In Proceedings of Supercomputing ‘89, (Reno, NV; Nov. 13-17, 1989), ACM, New York, NY.
Posters and Poster Papers
Briesch, M., R. Boldi, D. Sobania, A. Lalejini, T. Helmuth, F. Rothlauf, C. Ofria, and L. Spector. 2024. Improving Lexicase Selection with Informed Down-Sampling. “Hot Off the Press” track. Genetic and Evolutionary Computation Conference (GECCO ‘24).
Boldi, R., A. Bao, M. Briesch, T. Helmuth, D. Sobania, L. Spector, and A. Lalejini. 2024. A Comprehensive Analysis of Down-sampling for Genetic Programming-based Program Synthesis. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ‘24 Companion). Association for Computing Machinery, New York, NY, USA.
Boldi, R., L. Ding, and L. Spector. 2024. Solving Deceptive Problems Without Explicit Diversity Maintenance. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ‘24 Companion). Association for Computing Machinery, New York, NY, USA.
Boldi, R., A. Bao, M. Briesch, T. Helmuth, D. Sobania, L. Spector, and A. Lalejini. 2023. The Problem Solving Benefits of Down-Sampling Vary by Selection Scheme. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ‘23 Companion). Association for Computing Machinery, New York, NY, USA, 527–530. (pdf)
Boldi, R., A. Lalejini, T. Helmuth, and L. Spector. 2023. A Static Analysis of Informed Down-Samples. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ‘23 Companion). Association for Computing Machinery, New York, NY, USA, 531–534. (pdf; preprint pdf)
Saini, A.K., L. Spector, and T. Helmuth. 2022. Environments with local scopes for modules in genetic programming. In GECCO ‘22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 598-601. (pdf)
Ding, L., R. Boldi, T. Helmuth, and L. Spector. 2022. Going faster and hence further with lexicase selection. In GECCO ‘22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 538-541. (pdf)
Saini, A. K. and L. Spector. 2021. GLEAM: Genetic Learning by Extraction and Absorption of Modules. In Proceedings of GECCO ‘21 Companion, pp. 263-264. DOI: https://doi.org/10.1145/3449726.3459544
Helmuth, T., L. Spector, and E. Pantridge. 2020. Counterexample-Driven Genetic Programming without Formal Specifications. In Proceedings of GECCO ‘20 Companion, pp. 239-240. DOI: https://doi.org/10.1145/3377929.3389983
Helmuth, T., E. Pantridge, G. Woolson, L. Spector. 2020. Transfer Learning of Genetic Programming Instruction Sets. In Proceedings of GECCO ‘20 Companion, pp. 241-242. DOI: https://doi.org/10.1145/3377929.3389988
McPhee, N. F., M. M. Casale, M. Finzel, T. Helmuth, L. Spector. 2017. Visualizing genetic programming ancestries using graph databases. In Proceedings of GECCO ’17 Companion, Berlin, Germany, July 15-19, 2017, 2 pages. DOI: http://dx.doi.org/10.1145/3067695.3075617. (pdf)
McPhee N. F., T. Helmuth, L. Spector. 2017. Using algorithm configuration tools to optimize genetic programming parameters: A case study. In Proceedings of GECCO ’17 Companion, Berlin, Germany, July 15-19, 2017, 2 pages. DOI: http://dx.doi.org/10.1145/3067695.3076097 (pdf)
DelRosso N., N. Derr, L. Spector, and S. Hews. 2016. Triggered Regeneration of Molecular Circuit Components to Implement Iterative DNA Strand Displacement Operations. Presented at: FNANO. 13th Annual Foundations of Nanoscience: Self-Assembled Architectures and Devices; 2016 April 11-14; Snowbird, UT
DelRosso N., N. Derr, L. Spector, and S. Hews. 2016. Triggered Regeneration of Molecular Circuit Components to Implement Iterative DNA Strand Displacement Operations. Presented at: DNA22. 22nd International Conference on DNA Computing and Molecular Programming; 2016 September 4-8; Munich, Germany
Spector, L., and T. Helmuth. 2014. Effective Simplification of Evolved Push Programs Using a Simple, Stochastic Hill-climber. In Companion Publication of the 2014 Genetic and Evolutionary Computation Conference, GECCO’14 Companion. ACM Press. (pdf)
La Cava, W., L. Spector, K. Danai, and M. Lackner. 2014. Evolving differential equations with developmental linear genetic programming and epigenetic hill climbing. In Companion Publication of the 2014 Genetic and Evolutionary Computation Conference, GECCO’14 Companion. ACM Press.
Spector, L., and T. Helmuth. 2012. Empirical Investigation of Size-Based Tournaments for Node Selection in Genetic Programming. In Companion Publication of the 2012 Genetic and Evolutionary Computation Conference, GECCO’12 Companion. ACM Press. pp. 1485-1486. (pdf)
McCaffrey, Anthony J., and L. Spector. 2011. Innovation is Built on the Obscure: Innovation-Enhancing Software for Uncovering the Obscure. Poster paper, The 8th ACM Conference on Creativity and Cognition.
Spector, L., T. Helmuth, and K. Harrington. 2011. Fecundity and Selectivity in Evolutionary Computation. In GECCO’11 Posters, Genetic and Evolutionary Computation Conference. ACM Press. pp. 129-130. (pdf)
Niekum, S., L. Spector, and A. Barto. 2011. Evolution of Reward Functions for Reinforcement Learning. In GECCO’11 Posters, Genetic and Evolutionary Computation Conference. ACM Press. pp. 177-178. (pdf)
Rattermann, M. J., L. Spector and J. Grafman. 1996. Total and Partial-Order Planning: Application of Results from Artificial Intelligence to Children and Lesioned Adults. Poster presentation. The Eighteenth Annual Meeting of the Cognitive Science Society.
Spector, L. 1995. Evolving Control Structures with Automatically Defined Macros. Poster presentation. Genetic Programming Workshop at the Sixth International Conference on Genetic Algorithms.
Spector, L., M.J. Rattermann and K. Prentice. 1995. Total and partial-order planning: Application of results from artificial intelligence to children. Poster presented at the biennial meeting of the Society for Research in Child Development.
Spector, L. 1990. An Abstraction-Partitioned Model for Reactive Planning. Poster presentation. University of Maryland Systems Research Center.
Additional Scientific Publications
Helmuth, T., and L. Spector. 2015. Detailed Problem Descriptions for General Program Synthesis Benchmark Suite. University of Massachusetts, Amherst, Computer Science Technical Report UM-CS-2015-006. (online)
Spector, L., C. Perry, J. Klein, and M. Keijzer. 2004. Push 3.0 Programming Language Description. Hampshire College Cognitive Science Technical Report HC-CSTR-2004-02. (pdf)
Spector, L., E. Anderson, J. Miller, L. Sizer, and N. Stillings. 2004. Hampshire College School of Cognitive Science - Self Study Report. Hampshire College Cognitive Science Technical Report HC-CSTR-2004-01. (pdf)
Crawford-Marks, R., L. Spector, and J. Klein. 2004. Virtual Witches and Warlocks: A Quidditch Simulator and Quidditch-Playing Teams Coevolved via Genetic Programming. In Late-Breaking Papers of GECCO-2004, the Genetic and Evolutionary Computation Conference. Published by the International Society for Genetic and Evolutionary Computation. (pdf, Raphael’s page on the project, additional movies).
Spector, L., C. Perry, and J. Klein. 2003. Push 2.0 Programming Language Description. (html)
Robinson, A., and L. Spector. 2002. Using Genetic Programming with Multiple Data Types and Automatic Modularization to Evolve Decentralized and Coordinated Navigation in Multi-Agent Systems. In Late-Breaking Papers of GECCO-2002, the Genetic and Evolutionary Computation Conference. Published by the International Society for Genetic and Evolutionary Computation. (pdf)
Spector, L., R. Moore, and A. Robinson. 2001. Virtual Quidditch: A Challenge Problem for Automatically Programmed Software Agents. In E.D. Goodman, editor, Late-Breaking Papers of GECCO-2001, the Genetic and Evolutionary Computation Conference. Published by the International Society for Genetic and Evolutionary Computation. (pdf).
Barnum, H., H. J. Bernstein, and L. Spector. 2000. Quantum circuits for OR and AND of OR’s. Technical Report CSTR-00-014, Department of Computer Science, University of Bristol, August 2000. (Gzipped PostScript)
Spector, L, H. Barnum, H.J. Bernstein, and N. Swamy. 1999. Abstract for Invited Presentation: Quantum Computing and AI. In Proceedings of the Sixteenth National Conference on Artificial Intelligence, AAAI-99, AAAI Press.
Spector, L., H. Barnum, H.J. Bernstein, and N. Swamy. 1999. Finding a Better-than-Classical Quantum AND/OR Algorithm using Genetic Programming. In Proceedings of the 1999 Congress on Evolutionary Computation, pp. 2239-2246. IEEE Press. (postscript, pdf)
Barnum, H., Bernstein, H. J., and Spector, L. 1999. Better-than-classical Circuits for OR and AND/OR Found Using Genetic Programming. Los Alamos Preprint Archive, http://xxx.lanl.gov/abs/quant-ph/9907056
Luke, S., L. Spector, and D. Rager. 1996. Ontology-Based Knowledge Discovery on the World-Wide Web. In_Working Notes of the AAAI-96 Workshop on Internet-based Information Systems_. (pdf)
Luke, S., and L. Spector. 1996. Evolving Graphs and Networks with Edge Encoding: Preliminary Report. In Koza, John R. (editor), Late-Breaking Papers at the Genetic Programming 1996 Conference. Palo Alto, CA: Stanford Bookstore (ISBN 0-18-201-031-7). (pdf)
Spector, L. 1995. Evolving Control Structures with Automatically Defined Macros. Working Notes of the AAAI Fall Symposium on Genetic Programming. The American Association for Artificial Intelligence. pp. 99-105. (postscript, pdf)
Spector, L., and A. Alpern. 1995. Induction and Recapitulation of Deep Musical Structure. In Working Notes of the IJCAI-95 Workshop on Artificial Intelligence and Music. pp. 41-48. (postscript, pdf)
Spector, L. 1994. Artificial Intelligence as the Liberal Arts of Computer Science. In Working Notes of the AAAI Fall Symposium on Improving the Instruction of Introductory AI. The American Association for Artificial Intelligence. pp. 31-33.
Spector, L. 1992. Supervenience in Dynamic-World Planning, Doctoral dissertation. CS-TR-2899, UMIACS-TR-92-55, Department of Computer Science, University of Maryland. (Description and availability)
Spector, L., B. Andersen, J. Hendler, B. Kettler, E. Schwartzman, C. Woods, and M. Evett. 1992. Knowledge Representation in PARKA - Part 2: Experiments, Analysis, and Enhancements. CS-TR-2837, UMIACS-TR-92-16, Department of Computer Science, University of Maryland.
Spector, L. and J. Hendler. 1991. The Supervenience Architecture. In Proceedings of the AAAI Fall Symposium on Sensory Aspects of Robotic Intelligence. The American Association for Artificial Intelligence.
Spector, L. and J. Hendler. 1991. The Supervenience Architecture. In The Proceedings of the IJCAI-91 Workshop on Theoretical and Practical Design of Rational Agents, Sydney, Australia.
Spector, L. and J. Hendler. 1990. Knowledge Strata: Reactive Planning with a Multi-level Architecture. UMIACS-TR-90-140, CS-TR-2564, Department of Computer Science, University of Maryland.
Spector, L., J. Hendler, and M. Evett. 1990. Knowledge Representation in PARKA. UMIACS-TR-90-23, CS-TR-2410, Department of Computer Science, University of Maryland.
Evett, M., J. Hendler, and L. Spector. 1990. PARKA: Parallel Knowledge Representation on the Connection Machine. UMIACS-TR-90-22, CS-TR-2409, Department of Computer Science, University of Maryland.
Spector, L., J. Hendler, J. Canning, and A. Rosenfeld. 1988. Symbolic Model/Image Matching in Expert Vision Systems. CAR-TR-370, CS-TR-2060, University of Maryland Center for Automation Research.
Tutorials with published slides
Push. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2021. Slides published in GECCO ‘21 Companion, by the Association for Computing Machinery.
Push. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2020. Slides published in GECCO ‘20 Companion, by the Association for Computing Machinery.
Push. With N. F. McPhee. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2019. Slides published in GECCO ‘19 Companion, by the Association for Computing Machinery.
Expressive Genetic Programming: Concepts and Applications. With N. F. McPhee. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2018. Slides published in GECCO ‘18 Companion, by the Association for Computing Machinery.
Expressive Genetic Programming: Concepts and Applications. With N. F. McPhee. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2017. Slides published in GECCO ‘17 Companion, http://dx.doi.org/10.1145/3067695.3067699. (pdf)
Expressive Genetic Programming: Concepts and Applications. With N. F. McPhee. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2016. (pdf)
Expressive Genetic Programming. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2015.
Expressive Genetic Programming. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2014.
Expressive Genetic Programming. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2013.
Expressive Genetic Programming. Tutorial, 12th International Conference on Parallel Problem Solving From Nature (PPSN), September, 2012.
Expressive Genetic Programming. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2012.
Evolving Quantum Computer Algorithms. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2011.
Evolving Quantum Computer Algorithms. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2010.
Evolving Quantum Computer Algorithms. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2009.
Quantum Computing. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2008.
Quantum Computing. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2007.
Quantum Computing. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2006.
Quantum Computing. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2005.
Automated Invention by Means of Genetic Programming. Tutorial, with John Koza, Nineteenth National Conference on Artificial Intelligence (AAAI), July 25, 2004.
Quantum Computing. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2003.
Quantum Computing for Genetic Programmers. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 2002.
Quantum Computing. Tutorial, Genetic and Evolutionary Computation Conference (GECCO), July, 1999.
Newspaper Op-Ed
And now, digital evolution. In The Boston Globe, August 29, 2005. (local copy)
Published Letters
Letter to the editor, The Daily Hampshire Gazette, regarding local taxes, May 30, 2009.
Letter to the editor, The Daily Hampshire Gazette, regarding funding for public education, May 19, 2006.
Letter to the editor, New York Times, regarding warrantless surveillance, March 10, 2006. http://www.nytimes.com/2006/03/10/opinion/l10abuse.html?_r=1&oref=slogin&pagewanted=print
Letter to the editor, Scientific American, regarding nanobots, January, 2002.
Letter to the editor, Circuits section, New York Times, regarding robotic pets, May 11, 2000. http://query.nytimes.com/gst/fullpage.html?res=9407E1D9163BF932A25756C0A9669C8B63
Letter to the editor, IEEE Intelligent Systems, regarding quantum computing, September/October, 1999.
Quotes and Mentions
Quanta Magazine, “Mathematical Simplicity May Drive Evolution’s Speed,” by Jordana Cepelewicz. November 29, 2018. https://www.quantamagazine.org/computer-science-and-biology-explore-algorithmic-evolution-20181129/
Sentient interview for “Experts weigh in on the future of AI and evolutionary algorithms.” July, 2018. https://www.sentient.ai/labs/experts/ or https://www.youtube.com/watch?v=UWoWBiMowLI
The Boston Globe, “Possible cheating uncovered in popular Harvard computer class,” by Travis Andersen and Brian MacQuarrie. May 5, 2017. https://www.bostonglobe.com/metro/2017/05/04/possible-cheating-uncovered-popular-harvard-computer-class/4Wu2EfzWMEwXveBuuo9qFJ/story.html
Harvard Business Review, “There Will Always Be Limits to How Creative a Computer Can Be,” by Tony McCaffrey. April 24, 2017. https://hbr.org/2017/04/there-will-always-be-limits-to-how-creative-a-computer-can-be
WFCR, National Public Radio, “Rethinking Computer Intelligence,” by Karen Brown, radio story. June 17, 2014. http://nepr.net/news/2014/06/17/rethinking-computer-intelligence/
Ars Technica website, “Scientific computing’s future: Can any coding language top a 1950s behemoth?,’” by Lee Phillips. May 7, 2014. http://arstechnica.com/science/2014/05/scientific-computings-future-can-any-coding-language-top-a-1950s-behemoth/
The Technoskeptic podcast, “The Future of AI.” Interview. July 15, 2015. https://thetechnoskeptic.com/podcast001/
New Scientist magazine, “Wolf packs don’t need to cooperate to make a kill,” by Michael Marshall. Co-authored paper cited; co-author quoted. October 26, 2011. http://www.newscientist.com/article/mg21228354.700-wolf-packs-dont-need-to-cooperate-to-make-a-kill.html?DCMP=OTC-rss&nsref=online-news
WFCR, National Public Radio, “Hampshire Prof. Wins Grant to Create Computer Software That Can Evolve On Its Own,” by Fred Bever, radio story. September 6, 2010.
The Daily Hampshire Gazette, on the politics of software choices. “Hampshire takes lead on software,’’ by Stacey Butterfield. November 24, 2001.
Technology Research News, on the use of digital organisms in the study of evolutionary dynamics. “Virtual beings boost evolutionary theory,” by Ted Smalley Bowen. Oct 10, 2001. http://www.trnmag.com/Stories/2001/101001/Virtual_beings_boost_evolutionary_theory_101001.html
The Chronicle of Higher Education, on open-source software. “Hampshire College Favors Noncommercial Web Software Open to All.” Wednesday, October 3, 2001. http://chronicle.merit.edu/free/2001/10/2001100301t.htm
The Orlando Sentinel, on robotic pets. “They Bark, They Byte. Robotic Rovers Are The Rage – Woof It Up With Our Computerized-Pets Guide.” Friday, December 8, 2000.
Details magazine, on the possibility of computers having senses of humor. “Take My Hard Drive… Please; A computer may have beaten chess champion Garry Kasparov, but will one ever be able to tell a joke?” March, 2000.
The Daily Hampshire Gazette, on the importance of computers in the 20th century. “It was a century for invention.” January 1/2, 2000.
Salon.com on-line magazine, on genetic programming applications to quantum computing and jazz composition. “Software that Writes Software.” August 10, 1999. http://www.salon.com/tech/feature/1999/08/10/genetic_programming/index.html
Scientific American, on the use of “cultures” in genetic programming and on ontogenetic programming. “Programming With Primordial Ooze.” October, 1996.