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Papers

[127] Spears, W., and Prager, S. (to appear) Evolutionary search for understanding movement dynamics on mixed networks. Geoinformatica.

[126] Levine, G., Kuter, U., Rebguns, A., Green, D., and Spears, D. (to appear) Learning and verifying safety constraints for planners in a knowledge-impoverished system. Computational Intelligence.

[125] Zhang, X. et al. (to appear) An ensemble architecture for learning complex problem-solving techniques from demonstration. Transactions on Intelligent Systems and Technology.

[124] Diersen, S., Lee, E., Spears, D., Chen, P., and Wang, L. (2011) Classification of seismic windows using artificial neural networks. Proceedings of the ICCS Workshop on Data Mining in Earth System Science.

[123] Rebguns, A., Spears, D., Anderson-Sprecher, R., and Kletsov, A. (2010) A theoretical framework for estimating swarm success probability using scouts. International Journal of Swarm Intelligence Research, 1 (4), 17–45.

[122] Zarzhitsky, D., Spears, D., and Thayer, D. (2010) Experimental studies of swarm robotic chemical plume tracing using computation fluid dynamics simulations. International Journal of Intelligence Computing and Cybernetics, 3 (4), 631–671.

[121] Spears, W., Green, D., and Spears, D. (2010) Biases in particle swarm optimization. International Journal of Swarm Intelligence Research, 1 (2), 34–54.

[120] Shaw, L., Spears, W., Billings, L., and Maxim, P. (2010) Effective vaccination policies. Information Sciences, 180 (19), 3728–3744.

[119] Frey, C. L., Zarzhitsky, D., and Spears, D. (2009) A physics-based framework for distributed control of mobile sensor networks in the marine environment. Sea Technology Magazine.

[118] Maxim, P., and Spears, W. (2009) Robotic Uniform Coverage of Arbitrary-Shaped Connected Regions. Carpathian Journal of Electronic and Computer Engineering, 2 (1).

[117] Hettiarchchi, S., and Spears, W. (2009) Distributed adaptive swarm for obstacle avoidance. International Journal of Intelligent Computing and Cybernetics, 2 (4), Special Issue on Swarm Robotics, pp. 644-671.

[116] Spears, D., Thayer, D., and Zarzhitsky, D. (2009) Foundations of swarm robotic chemical plume tracing from a fluid dynamics perspective. International Journal of Intelligent Computing and Cybernetics, 2 (4), Special Issue on Swarm Robotics, pp. 745-785. This paper won the IJICC journal 2009 "highly commended paper" award.

[115] Prager, S. and Spears, W. (2009) A hybrid evolutionary-graph approach for finding functional network paths. Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.

[114] Maxim, P., Spears, W., and Spears, D. (2009) Robotic chain formations. In Proceedings of the IFAC Workshop on Networked Robotics (NetRob'09).

[113] Agassounon, W., Spears, W., Welsh, R., Zarzhitsky, D., and Spears, D. (2009) Toxic plume source localization in urban environments using collaborating robots. IEEE Conference on Technologies for Homeland Security. Poster session.

[112] Spears, D., Kerr, W., and Spears, W. (2009) Fluid-like swarms with predictable macroscopic behavior. Lecture Notes in Computer Science, Volume 4324.

[111] Levine, G., Kuter, U., Van Sloten, K., DeJong, G., Green, D., Rebguns, A., and Spears, D. (2009) Using qualitative domain proportionalities for learning mission safety in airspace operations. In the Proceedings of the IJCAI'09 Workshop on Learning Structural Knowledge From Observations.

[110] Zhang, X. et al. (2009) An ensemble learning and problem solving architecture for airspace management. In the Proceedings of the 21st Conference on Innovative Applications of Artificial Intelligence.

[109] Hettiarchchi, S., Maxim, P., and Spears, W. (2008) An architecture for adaptive swarms. In Robotics Research Trends. Nova Science Publishers, Inc.

[108] Hettiarachchi, S., Maxim, P., Spears, W., Spears, D. (2008) Connectivity of collaborative robots in partially observable domains. In Proceedings of the International Conference on Control, Automation, and Systems (COEX'08).

[107] Rebguns, A., Anderson-Sprecher, R., Spears, D., Spears, W., and Kletsov, A. (2008) Using scouts to predict swarm success rate. In Proceedings of the IEEE Swarm Intelligence Symposium (SIS'08). Best Student Paper Award.

[106] Maxim, P., Hettiarachchi, S., Spears, W., Spears, D., Hamman, J., Kunkel, T., and Speiser, C. (2008) Trilateration localization for multi-robot teams. In Sixth International Conference on Informatics in Control, Automation and Robotics, Special Session on Multi-Agent Robotic Systems (MARS'08).

[105] Frey, C. Zarzhitsky, D., Spears, W., Spears, D., Karlsson, C., Ramos, B., Hamann, J., and Widder, E. (2008) A physicomimetics control framework for swarms of autonomous vehicles. In Proceedings of the Oceans'08 Conference.

[104] Rebguns, A., Green, D., Levine, G., Kuter, U., and Spears, D. (2008) Inferring and applying safety constraints to guide an ensemble of planners for airspace deconfliction. In the Proceedings of the CP/ICAPS COPLAS'08 Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems.

[103] Kannan, S., Lee I., Lee, W., Sokolsky, O., Spears, D. and Spears, W. (2007) Anomaly and Misuse Detection in Network Traffic Streams - Checking and Machine Learning Approaches. Information Security Research, New Methods for Protecting Against Cyber Threats, Wiley, pp. 88-99.

[102] Spears, W., Hamann, J., Maxim, P., Kunkel, T., Heil, R., Zarzhitsky, D., Spears, D., and Karlsson, C. (2007) Where are you? In E. Sahin, W. Spears, and A. Winfield (Eds.), Second International Workshop on Swarm Robotics.

[101] Kuter, U., Levine, G., Green, D., Rebguns, A., Spears, D., and DeJong, G. (2007) Learning constraints via demonstration for safe planning. In Proceedings of the AAAI Workshop on Acquiring Planning Knowledge via Demonstration.

[100] Spears, D., Kerr, W., and Spears, W. (2006) Physics-based robot swarms for coverage problems. International Journal on Intelligent Control and Systems, 11(3).

[ 99] Wiegand, R., Potter, M., Sofge, D., and Spears, W. (2006) A generalized graph-based method for engineering swarm solutions to multiagent problems. In Parallel Problem Solving from Nature.

[ 98] Hettiarachchi, S. and Spears, W. (2006) DAEDALUS for agents with obstructed perception. In IEEE Mountain Workshop on Adaptive and Learning Systems. IEEE Press, Best Paper Award.

[ 97] Hettiarachchi, S., Spears, W., Kerr, W., Zarzhitsky, D., and Green, D. (2006) Distributed agent evolution with dynamic adaptation to local unexpected scenarios. In Second GSFC/IEEE Workshop on Radical Agent Concepts. Springer-Verlag.

[ 96] Kelly, C., Spears, D., Karlsson, C., and Polyakov, P. (2006) An ensemble of anomaly classifiers for identifying cyber attacks. In the Proceedings of the International SIAM Workshop on Feature Selection for Data Mining, Bethesda, MD. Also, republished in Critical Infrastructure Protection Research (Wiley Publishers).

[ 95] Shin, J., and Spears, D. (2006) The basic building blocks of malware. University of Wyoming Technical Report.

[ 94] Zarzhitsky, D., Spears, D., and Spears, W. (2005) Distributed robotics approach to chemical plume tracing. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'05).

[ 93] Kerr, W. and Spears, D. (2005) Robotic simulation of gases for a surveillance task. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'05).

[ 92] Zarzhitsky, D., Spears, D., and Spears, W. (2005) Swarms for chemical plume tracing. In Proceedings of the IEEE Swarm Intelligence Symposium (SIS'05).

[ 91] Spears, W., Spears, D., and Zarzhitsky, D. (2005, Invited) Physicomimetics positioning methodology for distributed autonomous systems. In GOMACTech-05 Intelligent Technologies.

[ 90] Hettiarachchi, S. and W. Spears (2005) Moving swarm formations through obstacle fields. In International Conference on Artificial Intelligence, Volume 1, pp. 97-103, CSREA Press.

[ 89] Spears, W., Heil, R., and Zarzhitsky, D. (2005) Artificial physics for mobile robot formations In Proceedings IEEE International Conference on Systems, Man, and Cybernetics (SMC'05), pp. 2287-2292.

[ 88] Spears, W., Zarzhitsky, D., Hettiarachchi, S., and Kerr, W. (2005, Invited) Strategies for multi-asset surveillance. In IEEE Networking, Sensing and Control.

[ 87] Zarzhitsky, D. and Spears, D. (2005) Swarm approach to chemical source localization. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC'05).

[ 86] Spears, D., Zarzhitsky, D., and Thayer, D. (2005) Multi-robot chemical plume tracing. Third International Workshop on Multi-Robot Systems.

[ 85] Spears, W., Spears, D., Hamann, J., and Heil, R. (2004) Distributed, physics-based control of swarms of vehicles. Autonomous Robots, 17 (2-3).

[ 84] Gordon-Spears, D. and Kiriakidis, K. (2004) Reconfigurable robot teams: Modeling and supervisory control. IEEE Transactions on Control Systems Technology 12 (5).

[ 83] Spears, W., Heil, R., Spears, D., and Zarzhitsky, D. (2004) Physicomimetics for mobile robot formations. Proceedings of the Third International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'04). Copyright ACM, (2004). This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in the proceedings of AAMAS'04.

[ 82] Zarzhitsky, D., Spears, D., Thayer, D., and Spears, W. (2004) Agent-based chemical plume tracing using fluid dynamics. Lecture Notes in Computer Science, Volume 3228, Springer Verlag.

[ 81] Spears, W., Spears, D., Heil, R., and Kerr, W. (2004) An overview of physicomimetics. In E. Sahin and W. Spears (Eds.), Lecture Notes in Computer Science, State-of-the-Art Series, Volume 3342.

[ 80] Kerr, W., Spears, D., Spears, W., and Thayer, D. (2004) Two formal gas models for multiagent sweeping and obstacle avoidance. Lecture Notes in Computer Science, Volume 3228, Springer Verlag.

[ 79] Spears, W., Spears, D., and Heil, R. (2004) A formal analysis of potential energy in a multiagent system. Lecture Notes in Computer Science, Volume 3228, Springer Verlag.

[ 78] Gordon-Spears, D. (2004) Assuring the behavior of adaptive agents. Book chapter in Agent Technology from a Formal Perspective. Kluwer.

[ 77] Zarzhitsky, D., Spears, D., Thayer, D. and Spears, W. (2004) A fluid dynamics approach to multi-robot chemical plume tracing. Proceedings of the Third International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'04).

[ 76] Gordon-Spears, D., and Spears, W. (2003) Analysis of a phase transition in a physics-based multiagent system. Lecture Notes in Computer Science, Volume 2699.

[ 75] Kiriakidis, K. and Gordon-Spears, D. (2003) Formal modeling and supervisory control of reconfigurable robot teams. Lecture Notes in Computer Science, Volume 2699.

[ 74] Kellogg, J., Bovais, C., Dahlburg, J., Foch, R., Gardner, J., Gordon, D., Hartley, R., Kamgar-Parsi, B., McFarlane, H., Pipitone, F., Ramamurti, R., Sciambi, A., Spears, W., Srull, D., and Sullivan, C. (2002) The NRL Micro Tactical Expendable (MITE) air vehicle. The Aeronautical Journal 106 (1062), 431-441.

[ 73]
Billings, L., Spears, W., and Schwartz, I. (2002) A Unified Prediction of Computer Virus Spread in Connected Networks. Physics Letters A, 297, 261-266.

[ 72] Spears, W. and Gordon, D. (2002) Evolution of strategies for resource protection problems. Book chapter in Theory and Applications of Evolutionary Computation: Recent Trends. Springer-Verlag.

[ 71] Kellogg, J., Bovais, C., Dahlburg, J., Foch, R., Gardner, J., Gordon, D., Hartley, R., Kamgar-Parsi, B., McFarlane, H., Pipitone, F., Ramamurti, R., Sciambi, A., Spears, W., Srull, D., and Sullivan, C. (2001) The NRL MITE air vehicle. In the Proceedings of the Bristol RPV/AUV Systems Conference.

[ 70] Kiriakidis, K. and Gordon, D. (2001) Supervision of multiple-robot systems. In the Proceedings of the American Control Conference (ACC'01).

[ 69] Gordon, D. (2001) APT Agents: Agents that are adaptive, predictable, and timely. In Lecture Notes in Artificial Intelligence, Volume 1871. Springer-Verlag.

[ 68] Kiriakidis, K. and Gordon, D. (2001) Adaptive supervisory control of multi-agent systems. In Lecture Notes in Artificial Intelligence, Volume 1871. Springer-Verlag.

[ 67] Spears, W., Billings, L., and Schwartz, I. (2001) Modeling viral epidemiology in connected networks. NRL Memorandum Report NRL/MR/6700-01-8537.

[ 66] Gordon, D. (2000) Asimovian adaptive agents. Journal of Artificial Intelligence Research, Vol. 13. This paper won the NRL Alan Berman Publication award.

[ 65] Spears, W. and Gordon, D. (2000) Evolving finite-state machine strategies for protecting resources. In the Proceedings of ISMIS'00.

[ 64] Spears, W. (2000) The Equilibrium and Transient Behavior of Mutation and Recombination. Proceedings of Foundations of Genetic Algorithms.

[ 63] Gordon, D. and Kiriakidis, K. (2000) Adaptive supervisory control of interconnected discrete event systems. In the Proceedings of the IEEE International Conference on Control Applications (ICCA'00)

[ 62] Gordon, D. and Kiriakidis, K. (2000) Design of adaptive supervisors for discrete event systems via learning. In the Proceedings of the International Mechanical Engineering Congress and Exposition (IMECE'00)

[ 61] Spears, W. & Gordon, D. (1999) Using Artificial Physics to control agents. In Proceedings of IEEE International Conference on Information, Intelligence, and Systems (ICIIS'99).

[ 60] Gordon, D., Spears, W., Sokolsky, O., & Lee, I. (1999) Distributed spatial control, global monitoring and steering of mobile physical agents. In Proceedings of IEEE International Conference on Information, Intelligence, and Systems (ICIIS'99).

[ 59] Spears, W. (1999) Aggregating models of evolutionary algorithms. In Proceedings of the Conference on Evolutionary Computation.

[ 58] Spears, W. (1999) An overview of multidimensional visualization techniques. In Proceedings of the Genetic and Evolutionary Computation Conference.

[ 57] Spears, W. (1998) A compression algorithm for probability transition matrices. SIAM Matrix Analysis and Applications, Volume 20, #1, 60-77.

[ 56] Gordon, D. (1998) Well-behaved Borgs, Bolos, and Berserkers. In the Proceedings of the Fifteenth International Conference on Machine Learning (ICML'98).

[ 55] Spears, W. and De Jong, K. (1998) Dining with GAs: Operator Lunch theorems. In Proceedings of Foundations of Genetic Algorithms.

[ 54] Kennedy, J. and Spears, W. (1998) Matching algorithms to problems: An experimental test of the particle swarm and some genetic algorithms on the Multimodal Problem Generator. Proceedings of the IEEE Int'l Conference on Evolutionary Computation.

[ 53] Gordon, D., Subramanian, D., Haught, M., Kobayashi, R., and Marshall, S. (1998) Modeling individual differences in learning on a navigation task. In the Proceedings of the Twentieth Annual Meeting of the Cognitive Science Society. PDF Figures 1-10 PDF Figures 11-20

[ 52] Spears, W. (1998) The role of mutation and recombination in evolutionary algorithms. Ph.D. Dissertation, George Mason University, Fairfax, Virginia.

[ 51] Gordon, D. (1998) An algorithm to find minimal sound and complete partitions for model checking. NCARAI Technical Report AIC-98-010.

[ 50] Spears, W. (1997) Recombination parameters, In The Handbook of Evolutionary Computation, T. Baeck, D. Fogel and Z. Michalewicz (editors), IOP Publishing and Oxford University Press.

[ 49] Deb, K. and Spears, W. (1997) Speciation methods, In The Handbook of Evolutionary Computation, T. Baeck, D. Fogel and Z. Michalewicz (editors), IOP Publishing and Oxford University Press. This paper isn't available yet, although a portion entitled "Speciation using tag bits" is available here:

[ 48] Gordon, D. & Subramanian, D. (1997) A cognitive model of learning to navigate. In Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society.

[ 47] De Jong, K., Potter, M., and Spears, W. (1997) Using problem generators to explore the effects of epistasis. In Proceedings of the Int'l Conference on Genetic Algorithms.

[ 46] Spears, W. (1996) Simulated annealing for hard satisfiability problems. In Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, David S. Johnson and Michael A. Trick (eds.), DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Volume 26, American Mathematical Society, 533-558.

[ 45] Spears, W. and De Jong, K. (1996) Analyzing GAs using Markov chains with semantically ordered and lumped states. In Proceedings of Foundations of Genetic Algorithms.

[ 44] Spears, W. (1996) A NN algorithm for Boolean satisfiability problems. In Proceedings of the 1996 International Conference on Neural Networks, 1121-1126.

[ 43] Gordon, D. & Subramanian, D. (1996) Cognitive modeling of action selection learning. In Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society.

[ 42] Gordon, D. & Subramanian, D. (1996) A comparison of action selection learning methods. In Proceedings of the Third International Workshop on Multistrategy Learning.

[ 41] Gordon, D. & desJardins, M. (1995) Evaluation and selection of biases in machine learning. Special issue on bias evaluation and selection. Machine Learning, 20(1/2), 5-22.

[ 40] Gordon, D., & Perlis, D. (1995) Explicitly biased generalization. Chapter 13 in Goal-Driven Learning, edited by A. Ram and D. Leake. (Reprint of 1989 Computational Intelligence article)

[ 39] Rao, R. B., Gordon, D., & Spears, W. (1995) For every generalization action, is there really an equal and opposite reaction? Analysis of the Conservation Law for generalization performance. In Proceedings of the Twelfth International Conference on Machine Learning., 471-479.

[ 38] Spears, W. (1995) Adapting crossover in evolutionary algorithms. Proceedings of the Evolutionary Programming Conference, 367-384.

[ 37] Gordon, D. F., Tag, P. M., & Bankert, R. L. (1995) Unsupervised classification procedures applied to satellite cloud data NCARAI Technical Report AIC-95-005.

[ 36] De Jong, K., Spears, W., and Gordon, D. (1994) Using Markov chains to analyze GAFOs. In Proceedings of Foundations of Genetic Algorithms, 115-137. B/W Figures PDF Grey Scale Figures PDF

[ 35] Spears, W. (1994) Simple subpopulation schemes. In Proceedings of the Evolutionary Programming Conference, 296-307.

[ 34] Drapkin, J., Gordon, D., Kraus, S., Miller, M., Nirkhe, M., and Perlis, D. (1994) Calibrating, counting, grounding, grouping. In working notes of the AAAI94 Fall Symposium on ``Control of the Physical World by Intelligent Agents.''

[ 33] Gordon, D., Tag, P., and Bankert, R. (1994) A test of an unsupervised machine learning procedure applied to cloud classification data. (Abstract) In Proceedings of the AIRIES94 Workshop.

[ 32] Spears, W. and Gordon, D. (1994) A simpler look at consistency (Technical Report AIC-94-018). Washington, DC: Naval Research Laboratory, Navy Center for Applied Research on Artificial Intelligence.

[ 31] De Jong, K., Spears W., Gordon D. (1993) Using genetic algorithms for concept learning. Machine Learning, 13 (2/3), 161-188. This paper won the NRL Alan Berman Publication award.

[ 30] Gordon, D. and Subramanian, D. (1993) A multistrategy learning scheme for agent knowledge acquisition. Informatica, 17, 331-346.

[ 29] Spears, W., De Jong, K., Baeck, T., Fogel, D., and de Garis, H. (1993) An overview of evolutionary computation. In Proceedings of the European Conference on Machine Learning, Volume 667, 442-459.

[ 28] Gordon D. and Subramanian D. (1993) A multistrategy learning scheme for assimilating advice in embedded agents. In Proceedings of the Second International Workshop on Multistrategy Learning (pp. 218-233). Harpers Ferry, WV: George Mason University.

[ 27] De Jong, K. and Spears, W. (1993) On the state of evolutionary computation. In Proceedings of the Int'l Conference on Genetic Algorithms, 618-623.

[ 26] Spears, W. (1993) A NN algorithm for hard satisfiability problems (Technical Report AIC-93-014). Washington, DC: Naval Research Laboratory, Navy Center for Applied Research on Artificial Intelligence.

[ 25] Spears, W. (1993) Simulated annealing for hard satisfiability problems (Technical Report AIC-93-015). Washington, DC: Naval Research Laboratory, Navy Center for Applied Research on Artificial Intelligence.

[ 24] De Jong, K. and Spears, W. (1992) A formal analysis of the role of multi-point crossover in genetic algorithms. Annals of Mathematics and Artificial Intelligence, 5 (1), 1-26.

[ 23] Spears, W. (1992) Crossover or mutation? In Proceedings of Foundations of Genetic Algorithms Workshop, 221-237.

[ 22] Spears, W. and Gordon, D. (1992) Is consistency harmful? In Proceedings of the Workshop on Biases in Inductive Learning at ML92.

[ 21] Grefenstette, J., De Jong, K., and Spears, W. (1992) Competition-based learning. Chapter 6 in Foundations of Knowledge Acquisition: Machine Learning, 203-225. Alan Meyrowitz and Susan Chipman (editors), Kluwer Academic Publishers.

[ 20] Spears, W. and De Jong, K. (1992) Using genetic algorithms for supervised concept learning. Chapter in Artificial Intelligence Methods and Applications, Nikolaos G. Bourbakis (editor), World Scientific.

[ 19] Gordon, D. (1992) Queries for bias testing. In Proceedings of the Workshop on Problem Reformulation and Representation Change, Asilomar, CA.

[ 18] Spears, W. (1992) Adapting crossover in a genetic algorithm (Technical Report AIC-92-025). Washington, DC: Naval Research Laboratory, Navy Center for Applied Research on Artificial Intelligence.

[ 17] Spears, W. (1992) Probabilistic satisfiability (Technical Report AIC-92-026). Washington, DC: Naval Research Laboratory, Navy Center for Applied Research on Artificial Intelligence.

[ 16] De Jong, K. and Spears, W. (1991) Learning concept classification rules using genetic algorithms. In Proceedings of the Int'l Joint Conference on Artificial Intelligence, 651-656.

[ 15] Gordon D. (1991) An enhancer for reactive plans. Proceedings of the Eighth International Machine Learning Workshop (pp. 505-508). Evanston, IL: Morgan Kaufmann.

[ 14] Spears, W. and De Jong, K. (1991) On the virtues of parameterized uniform crossover. In Proceedings of the Int'l Conference on Genetic Algorithms, 230-236.

[ 13] Spears W. and Gordon D. (1991) Adaptive strategy selection for concept learning. In Proceedings of the First International Workshop on Multistrategy Learning (pp. 231-246). Harpers Ferry, WV: George Mason University.

[ 12] Spears, W. and Anand, V. (1991) A study of crossover operators in genetic programming. In Proceedings of the Sixth Int'l Symposium on Methodologies for Intelligent Systems, 409-418.

[ 11] Gordon, D. (1991) Improving the comprehensibility, accuracy and generality of reactive plans. In Proceedings of the Sixth Int'l Symposium on Methodologies for Intelligent Systems, 358-367.

[ 10] Gordon, D. (1991) Active bias testing and adjustment for concept learning. In IJCAI Workshop on Evaluating and Changing Representation in Machine Learning.

[  9] Gordon D. and Grefenstette J. (1990) Explanations of empirically derived reactive plans. In Proceedings of the Seventh International Machine Learning Conference (pp. 198-203). Austin, TX: Morgan Kaufmann.

[  8] Spears, W. and De Jong, K. (1990) Using genetic algorithms for supervised concept learning. In Proceedings of the IEEE AI Tools Conference, 335-341.

[  7] De Jong, K. and Spears, W. (1990) An analysis of the interacting roles of population size and crossover in genetic algorithms. In Proceedings of the Int'l Workshop Parallel Problem Solving from Nature, 38-47.

[  6] Spears, W. and De Jong, K. (1990) An analysis of multi-point crossover. In Proceedings of the Foundations of Genetic Algorithms Workshop, 301-315.

[  5] Spears, W. and De Jong, K. (1990) Using neural networks and genetic algorithms as heuristics for NP-complete problems. In Proceedings of the Int'l Joint Conference on Neural Networks, 118-121.

[  4] Gordon, D. (1990) Active bias adjustment for incremental, supervised concept learning. Ph.D. Thesis, University of Maryland, College Park, MD.

[  3] Spears, W. (1990) Using neural networks and genetic algorithms as heuristics for NP-complete problems. Masters Thesis, George Mason University, Fairfax, Virginia.

[  2] De Jong, K. and Spears, W. (1989) Using genetic algorithms to solve NP-complete problems. In Proceedings of the Int'l Conference on Genetic Algorithms, 124-132.

[  1] Gordon, D. (1989) Explicitly biased generalization. Computational Intelligence 5(10), 67-81.
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