ISLE Publications and Technical Reports


Additional publications by ISLE staff, but not sponsored by ISLE, are available at individuals' web pages.

2005

Langley, P., Shiran, O., Shrager, J., Todorovski, L., & Pohorille, A. (in press). Constructing explanatory process models from biological data and knowledge. AI in Medicine.

Langley, P., Choi, D., & Rogers, S. (2005). Interleaving learning, problem solving, and execution in the Icarus architecture (Technical Report). Computational Learning Laboratory, CSLI, Stanford University, CA.

Langley, P., Todorovski, L., Bridewell, & Dzeroski, S. (2005). Inductive process modeling (Technical Report). Computational Learning Laboratory, CSLI, Stanford University, CA.

Langley, P., & Choi, D. (2005). Learning recursive control programs from problem solving (Technical Report). Computational Learning Laboratory, CSLI, Stanford University, CA.

Langley, P. (in press). Cognitive architectures and general intelligent systems. AI Magazine.

Jones, R. M., & Langley, P. (in press). A constrained architecture for learning and problem solving. Computational Intelligence.

Asgharbeygi, N., Bay, S., Langley, P., & Arrigo, K. (in press). Inductive revision of quantitative process models. Ecological Modelling.

Langley, P. (2005). An adaptive architecture for physical agents. Proceedings of the 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (pp. 18-25). Compiegne, France: IEEE Computer Society Press.

Bridewell, W., Bani Asadi, N., Langley, P., & Todorovski, L. (2005). Reducing overfitting in process model induction. Proceedings of the Twenty-Second International Conference on Machine Learning (pp. 81-88). Bonn, Germany.

Choi, D., & Langley, P. (2005). Learning teleoreactive logic programs from problem solving. Proceedings of the Fifteenth International Conference on Inductive Logic Programming (pp. 51-68). Bonn, Germany: Springer.

Langley, P., & Rogers, S. (2005). An extended theory of human problem solving. Proceedings of the Twenty-Seventh Annual Meeting of the Cognitive Science Society. Stresa, Italy.

Asgharbeygi, N., Nejati, N., Langley, P., & Arai, S. (2005). Guiding inference through relational reinforcement learning. Proceedings of the Fifteenth International Conference on Inductive Logic Programming (pp. 20-37). Bonn, Germany: Springer.

Todorovski, L., Bridewell, W., Shiran, O., & Langley, P. (2005). Inducing hierarchical process models in dynamic domains. Proceedings of the Twentieth National Conference on Artificial Intelligence (pp. 892-897). Pittsburgh, PA: AAAI Press.

2004

Bridewell, W., Sanchez, J. N., & Langley, P. (2004). An interactive environment for the modeling and discovery of scientific knowledge (Technical Report). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Langley, P., & Rogers, S. (2004). Cumulative learning of hierarchical skills. Proceedings of the Third International Conference on Development and Learning. San Diego, CA: IEEE Press.

Asgharbeygi, N., Bay, S., Langley, P., & Arrigo, K. (2004). Computational revision of ecological process models. Proceedings of the Fourth International Workshop on Environmental Applications of Machine Learning (pp. 13-14). Bled, Slovenia.

Langley, P., Shrager, J., Asgharbeygi, N., Bay, S., & Pohorille, A. (2004). Inducing explanatory process models from biological time series Proceedings of the Ninth Workshop on Intelligent Data Analysis and Data Mining (pp. 85-90). Stanford, CA.

Langley, P., & Messina, E. (2004). Experimental studies of integrated cognitive systems. Proceedings of the Performance Metrics for Intelligent Systems Workshop. Gaithersburg, MD.

Langley, P. (2004). Cognitive architectures and the construction of intelligent agents. Proceedings of the AAAI-2004 Workshop on Intelligent Agent Architectures (pp. 82). Stanford, CA.

Langley, P., Arai, S., & Shapiro, D. (2004). Model-based learning with hierarchical relational skills. Proceedings of the ICML-2004 Workshop on Relational Reinforcement Learning. Banff, Alberta.

Langley, P., Cummings, K., & Shapiro, D. (2004). Hierarchical skills and cognitive architectures. Proceedings of the Twenty-Sixth Annual Conference of the Cognitive Science Society (pp. 779-784). Chicago, IL.

Choi, D., Kaufman, M., Langley, P., Nejati, N., & Shapiro, D. (2004). An architecture for persistent reactive behavior. Proceedings of the Third International Joint Conference on Autonomous Agents and Multi Agent Systems (pp. 988-995). New York: ACM Press.

Lavrac, N., Motoda, H., Fawcett, T., Holte, R., Langley, P., & Adriaans, P. (2004). Lessons learned from data mining applications and collaborative problem solving. Machine Learning, 57, 13-34.

Langley, P., Choi, D., & Shapiro, D. (2004). A cognitive architecture for physical agents (Technical Report). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Ichise, R., Shapiro, D., & Langley, P. (in press). Structured program induction from behavioral traces. IEICE Transactions on Information and Systems (in Japanese).

Schroedl, S., Wagstaff, K., Rogers, S., Langley, P., & Wilson, C. (2004). Mining GPS traces for map refinement. Knowledge Discovery and Data Mining, 9, 59-87.

Langley, P. (2004). Heuristics for scientific discovery: The legacy of Herbert Simon. In M. E. Augier & J. G. March (Eds.), Models of a Man: Essays in Memory of Herbert A. Simon. Cambridge, MA: MIT Press.

Thompson, C. A., Göker, M., & Langley, P. (2004). A personalized system for conversational recommendations. Journal of Artificial Intelligence Research, 21, 393-428.

2003

Todorovski, L., Dzeroski, S., Langley, P., & Potter, C. (2003). Using equation discovery to revise an Earth ecosystem model of carbon net production. Ecological Modelling, 170, 141-154.

Sanchez, J. N., & Langley, P. (2003). An interactive environment for scientific model construction. Proceedings of the Second International Conference on Knowledge Capture (pp. 138-145). Sanibel Island, FL: ACM Press.

George, D., Saito, K., Langley, P., Bay, S., & Arrigo, K. (2003). Discovering ecosystem models from time-series data. Proceedings of the Sixth International Conference on Discovery Science (pp. 141-152). Saporro, Japan: Springer.

Saito, K., George, D., Bay, S., & Shrager, J. (2003). Inducing biological models from temporal gene expression data. Proceedings of the Sixth International Conference on Discovery Systems. Sapporo, Japan.

Bay, S. D., & Schwabacher, M. (2003). Mining distance-based outliers in near linear time with randomization and a simple pruning rule. Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. PDF. Postscript.

Langley, P., George, D., Bay, S., & Saito, K. (2003). Robust induction of process models from time-series data. Proceedings of the Twentieth International Conference on Machine Learning (pp. 432-439).

Bay, S. D., Chrisman, L., Pohorille, A., & Shrager, J. (2003). Temporal aggregation bias and inference of causal regulatory networks. Proceedings of the IJCAI-2003 Workshop on Learning Graphical Models for Computational Genomics. Postscript. PDF.

Todorovski, L., Dzeroski, S., Langley, P., & Potter, C. (in press). Using equation discovery to revise an Earth ecosystem model of carbon net production. Ecological Modeling.

Maloof, M. A., Langley, P., Binford, T. O., Nevatia, R., & Sage, S. (2003). Improved rooftop detection in aerial images with machine learning. Machine Learning, 53, 157-191.

Bay, S. D., Shrager, J., Pohorille, A., & Langley, P. (2003). Revising regulatory networks: From expression data to linear causal models. Journal of Biomedical Informatics, 35, 289-297.

Langley, P., Shapiro, D., Aycinena, M., & Siliski, M. (2003). A value-driven architecture for intelligent behavior. Proceedings of the IJCAI-2003 Workshop on Cognitive Modeling of Agents and Multi-Agent Interactions (pp. 10-18). Acapulco, Mexico.

Yoo, J., Gervasio, M., & Langley, P. (2003). An adaptive stock tracker for personalized trading advice. Proceedings of the International Conference on Intelligent User Interfaces (pp. 197-203). Miami, Florida.

Chrisman, L., Langley, P., Bay, S., & Pohorille, A. (2003). Incorporating biological knowledge into evaluation of causal regulatory hypotheses. Proceedings of the Pacific Symposium on Biocomputing (pp. 128-139). Lihue, Hawaii.

2002

Langley, P., & Laird, J. E. (2002). Cognitive architectures: Research issues and challenges (Technical Report). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Saito, K., Bay, S., & Langley, P. (2002). Revising qualitative models of gene regulation (pp. 59-70). Proceedings of the Fifth International Conference on Discovery Science.

Langley, P. (2002). Lessons for the computational discovery of scientific knowledge. Proceedings of First International Workshop on Data Mining Lessons Learned (pp. 9-12). Sydney.

Bay, S. D., Shapiro, D. G., & Langley, P. (2002). Revising engineering models: Combining computational discovery with knowledge. Proceedings of the Thirteenth European Conference on Machine Learning (pp. 10-22). Helsinki, Finland.

Ichise, R., Shapiro, D. G., & Langley, P. (2002). Learning hierarchical skills from observation (pp. 247-258). Proceedings of the Fifth International Conference on Discovery Science.

Langley, P., Sanchez, J., Todorovski, L., & Dzeroski, S. (2002). Inducing process models from continuous data. Proceedings of the Nineteenth International Conference on Machine Learning (pp. 347-354). Sydney: Morgan Kaufmann.

Shapiro, D., & Langley, P. (2002). Separating skills from preference: Using learning to program by reward. Proceedings of the Nineteenth International Conference on Machine Learning (pp. 570-577). Sydney: Morgan Kaufmann.

Langley, P., Shrager, J., & Saito, K. (2002). Computational discovery of communicable scientific knowledge. In L. Magnani, N. J. Nersessian, & C. Pizzi (Eds.), Logical and Computational Aspects of Model-Based Reasoning. Dordrecht: Kluwer Academic.

Shrager, J., Langley, P., & Pohorille, A. (2002). Guiding revision of regulatory models with expression data. Proceedings of the Pacific Symposium on Biocomputing (pp. 486-497). Lihue, Hawaii.

2001

Saito, K., Langley, P., Grenager, T., Potter, C., Torregrosa, A., & Klooster, S. A. (2001). Computational revision of quantitative scientific models. Proceedings of the Fourth International Conference on Discovery Science (pp. 336-349). Washington, D.C.: Springer.

Kocabas, S., & Langley, P. (2001). An integrated framework for extended discovery in particle physics. Proceedings of the Fourth International Conference on Discovery Science (pp. 182-195). Washington, D.C.: Springer.

Dzeroski, S., & Langley, P. (2001). Computational discovery of communicable knowledge: Symposium report. Proceedings of the Fourth International Conference on Discovery Science (pp. 45-49). Washington, D.C.: Springer.

Kalton, A., Langley, P., Wagstaff, K., & Yoo, J. (2001). Generalized clustering, supervised learning, and data assignment. Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining (pp. 299-304). San Francisco: ACM Press.

Iba, W., & Langley, P. (2001). Unsupervised learning of probabilistic concept hierarchies. In G. Paliouras, V. Karkaletsis, & C. D. Spyropoulos (Eds)., Machine learning and its applications. Berlin: Springer.

Langley, P., Magnani, L., Cheng, P. C.-H., Gordon, A., Kocabas, S., & Sleeman, D. H. (2001). Computational models of historical scientific discoveries. Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society (p. 3). Edinburgh: Lawrence Erlbaum.

Schwabacher, M., & Langley, P. (2001). Discovering communicable scientific knowledge from spatio-temporal data. Proceedings of the Eighteenth International Conference on Machine Learning (pp. 489-496). Williamstown, MA: Morgan Kaufmann.

Shapiro, D., Langley, P., & Shachter, R. (2001). Using background knowledge to speed reinforcement learning in physical agents. Proceedings of the Fifth International Conference on Autonomous Agents (pp. 254-261). Montreal: ACM Press.

2000

Kocabas, S., & Langley, P. (2000). Computer generation of process explanations in nuclear astrophysics. International Journal of Human-Computer Studies, 53, 377-392.

1999

Iba, W., & Langley, P. (1999). Unsupervised learning of probabilistic concept hierarchies (Technical Report 99-1). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Langley, P. (1999). Concrete and abstract models of category learning. Proceedings of the Twenty-First Annual Conference of the Cognitive Science Society (pp. 288-293). Vancouver, BC: Lawrence Erlbaum.

Gervasio, M. T., Iba, W., & Langley, P. (1999). Learning user evaluation functions for adaptive scheduling assistance. Proceedings of the Sixteenth International Conference on Machine Learning (pp. 152-161). Bled, Slovenia: Morgan Kaufmann.

Langley, P., & Sage, S. (1999). Tractable average-case analysis of naive Bayesian classifiers. Proceedings of the Sixteenth International Conference on Machine Learning (pp. 220-228). Bled, Slovenia: Morgan Kaufmann.

Iba, W., & Gervasio, M. (1999). Adapting to user preferences in crisis response. Proceedings of the 1999 International Conference on Intelligent User Interfaces. Redondo Beach, CA.

1998

Langley, P., & Fehling, M. (1998). The experimental study of adaptive user interfaces (Technical Report 98-3). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Ali, K. M., Langley, P., Maloof, M. A., Binford, T. O., & Sage, S. (1998). Improving rooftop detection with interactive visual learning. Proceedings of the Image Understanding Workshop. Monterrey, CA: Morgan Kaufmann.

Kocabas, S., & Langley, P. (1998). Generating process explanations in nuclear astrophysics. Proceedings of the ECAI-98 Workshop on Machine Discovery (pp. 4-9). Brighton, UK.

Maloof, M. A., Langley, P., Binford, T. O., & Nevatia, R. (1998). Generalizing over aspect and location for rooftop detection. Proceedings of the Fourth IEEE Workshop on Applications of Computer Vision. Princeton, NJ: IEEE Press.

Iba, W., Gervasio, M., Langley, P., & Sage, S. (1998). Evaluating computational assistance for crisis response. Proceedings of the Twentieth Annual Conference of the Cognitive Science Society (pp. 514-519). Madison, WI: Lawrence Erlbaum.

Gervasio, M., Iba, W., & Langley, P. (1998). Learning to predict user operations for adaptive scheduling. Proceedings of the Fifteenth National Conference on Artificial Intelligence (pp. 721-726). Madison, WI: AAAI Press.

Yamauchi, B., Langley, P., Schultz, A. C., Grefenstette, J., & Adams, W. (1998). Magellan: An integrated adaptive architecture for mobile robotics (Technical Report 98-2). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Gervasio, M., Iba, W., & Langley, P. (1998). Case-based seeding for an interactive crisis response assistant. Proceedings of the AAAI-98 Workshop on Case-Based Reasoning Integrations. Madison, WI.

Maloof, M. A., Langley, P., Binford, T., & Sage, S. (1998). Improving rooftop detection in aerial images through machine learning (Technical Report 98-1). Institute for the Study of Learning and Expertise, Palo Alto, CA.

Gervasio, M., Iba, W., & Langley, P. (1998). Learning to predict user operations for adaptive scheduling. Proceedings of the Fifteenth National Conference on Artificial Intelligence (pp. 721-726). Madison, WI: AAAI Press.

Gervasio, M., Iba, W., Langley, P., & Sage, S. (1998). Interactive adaptation for crisis response. Proceedings of the AIPS-98 Workshop on Interactive and Collaborative Planning (pp. 29-36). Pittsburgh, PA.

1997

Blum, A., & Langley, P. (1997). Selection of relevant features and examples in machine learning. Artificial Intelligence, 97, 245-271.

Maloof, M. A., Langley, P., Sage, S., & Binford, T. (1997). Learning to detect rooftops in aerial images. Proceedings of the 1997 Image Understanding Workshop (pp. 835-845). New Orleans: Morgan Kaufmann.

Yamauchi, B., & Langley, P. (1997). Place recognition in dynamic environments. Journal of Robotic Systems, 14, 107-120.

Kohavi, R., Langley, P., & Yun, Y. (1997). The utility of feature weighting in nearest-neighbor algorithms. Proceedings of the Ninth European Conference on Machine Learning. Prague: Springer-Verlag.

Langley, P. (1997). Learning to sense selectively in physical domains. Proceedings of the First International Conference on Autonomous Agents (pp. 217-226). Marina del Rey, CA: ACM Press.

Langley, P., Pfleger, K., & Sahami, M. (1997). Lazy acquisition of place knowledge. Artificial Intelligence Review, 11, 315-342.

Langley, P., & Sage, S. (1997). Scaling to domains with irrelevant features. In R. Greiner (Ed.), Computational learning theory and natural learning systems (Vol. 4). Cambridge, MA: MIT Press.

1996

Yamauchi, B., & Langley, P. (1996). Place learning in dynamic real-world environments. Proceedings of RoboLearn-96: International Workshop for Learning in Autonomous Robots (pp. 123-129). Key West, FL.

Provan, G., Langley, P., & Binford, T.O. (1996). Probabilistic learning of three-dimensional object models. Proceedings of the Image Understanding Workshop (pp. 1403-1413). Palm Springs, CA: Morgan Kaufmann.

Langley, P. (October, 1996). Relevance and insight in experimental studies. IEEE Expert, 11-12.

1995

Langley, P. (1995). Order effects in incremental learning. In P. Reimann & H. Spada (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science. Oxford: Elsevier.

Langley, P., & Pfleger, K. (1995). Case-based acquisition of place knowledge. Proceedings of the Twelfth International Conference on Machine Learning (pp. 244-352). Lake Tahoe, CA: Morgan Kaufmann.

1994

Langley, P. (1994). Selection of relevant features in machine learning. Proceedings of the AAAI Fall Symposium on Relevance. New Orleans: AAAI Press.

Langley, P., Binford, T. O., & Levitt, T. S. (1994). Learning object models from visual observation and background knowledge. Proceedings of the Image Understanding Workshop. Monterrey, CA.

Bowyer, K. W., Hall, L. O., Langley, P., Bhanu, B., & Draper, B. A. (1994). Report of the AAAI fall symposium on machine learning and computer vision: What, why and how. Proceedings of the Image Understanding Workshop. Monterrey, CA.

Langley, P., & Sage, S. (1994). Induction of selective Bayesian classifiers. Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (pp. 399-406). Seattle, WA: Morgan Kaufmann.

Langley, P., & Sage, S. (1994). Oblivious decision trees and abstract cases. Working Notes of the AAAI94 Workshop on Case-Based Reasoning (pp. 113-117). Seattle, WA: AAAI Press.

Langley, P., Iba, W., & Shrager, J. (1994). Reactive and automatic behavior in plan execution. Proceedings of the Second International Conference on AI Planning Systems (pp. 299-304). Chicago: AAAI Press.

For more information, send electronic mail to langley@isle.org

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