| Year |
Citation |
Score |
| 2019 |
Langley P. Scientific discovery, causal explanation, and process model induction Mind & Society. 18: 43-56. DOI: 10.1007/S11299-019-00216-1 |
0.519 |
|
| 2018 |
Choi D, Langley P. Evolution of the Icarus Cognitive Architecture Cognitive Systems Research. 48: 25-38. DOI: 10.1016/J.Cogsys.2017.05.005 |
0.317 |
|
| 2017 |
Langley P. Interactive Cognitive Systems and Social Intelligence Ieee Intelligent Systems. 32: 22-30. DOI: 10.1109/Mis.2017.3121556 |
0.301 |
|
| 2015 |
Dinar M, Danielescu A, MacLellan C, Shah JJ, Langley P. Problem Map: An Ontological Framework for a Computational Study of Problem Formulation in Engineering Design Journal of Computing and Information Science in Engineering. 15. DOI: 10.1115/1.4030076 |
0.341 |
|
| 2015 |
Langley P, Arvay A. Heuristic induction of rate-based process models Proceedings of the National Conference On Artificial Intelligence. 1: 537-543. |
0.387 |
|
| 2014 |
Langley P, Meadows B, Gabaldon A, Heald R. Abductive understanding of dialogues about joint activities Interaction Studies. 15: 426-454. DOI: 10.1075/Is.15.3.04Lan |
0.355 |
|
| 2014 |
Langley P, Pearce C, Barley M, Emery M. Bounded rationality in problem solving: Guiding search with domain-independent heuristics Mind and Society. 13: 83-95. DOI: 10.1007/S11299-014-0143-Y |
0.314 |
|
| 2012 |
Blisard S, Carmichael T, Ding L, Finin T, Frost W, Graesser A, Hadzikadic M, Kagal L, Kruijff GJM, Langley P, Lester J, McGuinness DL, Mostow J, Papadakis P, Pirri F, et al. Reports of the AAAI 2011 fall symposia Ai Magazine. 33: 71-78. DOI: 10.1609/Aimag.V33I1.2391 |
0.326 |
|
| 2011 |
Langley P. The changing science of machine learning Machine Learning. 82: 275-279. DOI: 10.1007/S10994-011-5242-Y |
0.431 |
|
| 2011 |
Langley P, Bridewell W. Combining data-driven and knowledge-guided methods to induce interpretable physiological models Aaai Spring Symposium - Technical Report. 32-36. |
0.732 |
|
| 2010 |
Bridewell W, Langley P. Two kinds of knowledge in scientific discovery. Topics in Cognitive Science. 2: 36-52. PMID 25163620 DOI: 10.1111/J.1756-8765.2009.01050.X |
0.743 |
|
| 2009 |
Bridewell W, Borrett SR, Langley P. Supporting Innovative Construction of Explanatory Scientific Models Tools For Innovation. DOI: 10.1093/acprof:oso/9780195381634.003.0011 |
0.69 |
|
| 2009 |
Könik T, O’Rorke P, Shapiro D, Choi D, Nejati N, Langley P. Skill transfer through goal-driven representation mapping Cognitive Systems Research. 10: 270-285. DOI: 10.1016/J.Cogsys.2008.09.008 |
0.338 |
|
| 2009 |
Langley P, Choi D, Rogers S. Acquisition of hierarchical reactive skills in a unified cognitive architecture Cognitive Systems Research. 10: 316-332. DOI: 10.1016/J.Cogsys.2008.07.003 |
0.421 |
|
| 2009 |
Langley P, Laird JE, Rogers S. Cognitive architectures: Research issues and challenges Cognitive Systems Research. 10: 141-160. DOI: 10.1016/J.Cogsys.2006.07.004 |
0.34 |
|
| 2008 |
Cassimatis NL, Bello P, Langley P. Ability, breadth, and parsimony in computational models of higher-order cognition. Cognitive Science. 32: 1304-22. PMID 21585455 DOI: 10.1080/03640210802455175 |
0.414 |
|
| 2008 |
Bridewell W, Langley P, Todorovski L, Džeroski S. Inductive process modeling Machine Learning. 71: 1-32. DOI: 10.1007/S10994-007-5042-6 |
0.754 |
|
| 2007 |
Borrett SR, Bridewell W, Langley P, Arrigo KR. A method for representing and developing process models Ecological Complexity. 4: 1-12. DOI: 10.1016/J.Ecocom.2007.02.017 |
0.738 |
|
| 2006 |
Langley P, Shiran O, Shrager J, Todorovski L, Pohorille A. Constructing explanatory process models from biological data and knowledge. Artificial Intelligence in Medicine. 37: 191-201. PMID 16781850 DOI: 10.1016/J.Artmed.2006.04.003 |
0.489 |
|
| 2006 |
Langley P. Cognitive architectures and general intelligent systems Ai Magazine. 27: 33-34. DOI: 10.1609/Aimag.V27I2.1878 |
0.355 |
|
| 2006 |
Bridewell W, Sánchez JN, Langley P, Billman D. An interactive environment for the modeling and discovery of scientific knowledge International Journal of Human Computer Studies. 64: 1099-1114. DOI: 10.1016/J.Ijhcs.2006.06.006 |
0.731 |
|
| 2006 |
Asgharbeygi N, Langley P, Bay S, Arrigo K. Inductive revision of quantitative process models Ecological Modelling. 194: 70-79. DOI: 10.1016/J.Ecolmodel.2005.10.008 |
0.539 |
|
| 2006 |
Bridewell W, Langley P, Racunas S, Borrett S. Learning process models with missing data Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4212: 557-565. |
0.721 |
|
| 2005 |
Bridewell W, Asadi NB, Langley P, Todorovski L. Reducing overfitting in process model induction Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 81-88. DOI: 10.1145/1102351.1102362 |
0.747 |
|
| 2005 |
Ichise R, Shapiro D, Langley P. Structured program induction from behavioral traces Systems and Computers in Japan. 36: 49-59. DOI: 10.1002/Scj.V36:11 |
0.331 |
|
| 2004 |
Lavrač N, Motoda H, Fawcett T, Holte R, Langley P, Adriaans P. Introduction: Lessons learned from data mining applications and collaborative problem solving Machine Learning. 57: 13-34. DOI: 10.1023/B:Mach.0000035516.74817.51 |
0.419 |
|
| 2004 |
Schroedl S, Wagstaff K, Rogers S, Langley P, Wilson C. Mining GPS Traces for Map Refinement Data Mining and Knowledge Discovery. 9: 59-87. DOI: 10.1023/B:Dami.0000026904.74892.89 |
0.312 |
|
| 2003 |
Maloof MA, Langley P, Binford TO, Nevatia R, Sage S. Improved Rooftop Detection in Aerial Images with Machine Learning Machine Learning. 53: 157-191. DOI: 10.1023/A:1025623527461 |
0.346 |
|
| 2003 |
Todorovski L, Džeroski S, Langley P, Potter C. Using equation discovery to revise an Earth ecosystem model of the carbon net production Ecological Modelling. 170: 141-154. DOI: 10.1016/S0304-3800(03)00222-9 |
0.408 |
|
| 2002 |
Bay SD, Shrager J, Pohorille A, Langley P. Revising regulatory networks: from expression data to linear causal models. Journal of Biomedical Informatics. 35: 289-97. PMID 12968777 DOI: 10.1016/S1532-0464(03)00031-5 |
0.365 |
|
| 2002 |
Shrager J, Langley P, Pohorille A. Guiding revision of regulatory models with expression data. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 486-97. PMID 11928501 |
0.359 |
|
| 2001 |
Iba W, Langley P. Unsupervised learning of probabilistic concept hierarchies Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2049: 39-70. DOI: 10.1007/3-540-44673-7_3 |
0.422 |
|
| 2001 |
Langley P. The computational support of scientific discovery Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2049: 230-248. DOI: 10.1006/Ijhc.2000.0396 |
0.371 |
|
| 1997 |
Langley P, Provan GM, Smyth P. Machine Learning. 29: 91-101. DOI: 10.1023/A:1007467927290 |
0.491 |
|
| 1997 |
Langley P, Pfleger K, Sahami M. Lazy Acquisition of Place Knowledge Artificial Intelligence Review. 11: 315-342. DOI: 10.1023/A:1006545731094 |
0.409 |
|
| 1997 |
Blum AL, Langley P. Selection of relevant features and examples in machine learning Artificial Intelligence. 97: 245-271. DOI: 10.1016/S0004-3702(97)00063-5 |
0.397 |
|
| 1997 |
Langley P. Machine learning for adaptive user interfaces Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1303: 53-62. DOI: 10.1007/3540634932_3 |
0.364 |
|
| 1997 |
Yamauchi B, Langley P. Place recognition in dynamic environments Journal of Robotic Systems. 14: 107-120. DOI: 10.1002/(Sici)1097-4563(199702)14:2<107::Aid-Rob5>3.0.Co;2-W |
0.333 |
|
| 1996 |
Langley P. Empirical Methods in Artificial Intelligence: A Review Ai Magazine. 17: 95. DOI: 10.1609/Aimag.V17I3.1234 |
0.411 |
|
| 1996 |
Langley P. Relevance and insight in experimental studies Ieee Expert-Intelligent Systems and Their Applications. 11: 11-12. DOI: 10.1109/64.539009 |
0.394 |
|
| 1995 |
Langley P, Simon HA. Applications of machine learning and rule induction Communications of the Acm. 38: 54-64. DOI: 10.1145/219717.219768 |
0.564 |
|
| 1993 |
Nordhausen B, Langley P. An Integrated Framework for Empirical Discovery Machine Learning. 12: 17-47. DOI: 10.1007/Bf00993059 |
0.397 |
|
| 1990 |
Langley P. Editorial: Advice to Machine Learning Authors Machine Learning. 5: 233-237. DOI: 10.1023/A:1022647305786 |
0.355 |
|
| 1990 |
Langley P. Approaches to learning and representation Behavioral and Brain Sciences. 13: 500-501. DOI: 10.1017/S0140525X00079875 |
0.374 |
|
| 1990 |
Fisher D, Langley P. The Structure and Formation of Natural Categories Psychology of Learning and Motivation - Advances in Research and Theory. 26: 241-284. DOI: 10.1016/S0079-7421(08)60056-0 |
0.429 |
|
| 1989 |
Langley P. Toward a Unified Science of Machine Learning Machine Learning. 3: 253-259. DOI: 10.1023/A:1022689616458 |
0.425 |
|
| 1989 |
Langley P, Zytkow JM. Data-driven approaches to empirical discovery Artificial Intelligence. 40: 283-312. DOI: 10.1016/0004-3702(89)90051-9 |
0.397 |
|
| 1989 |
Gennari JH, Langley P, Fisher D. Models of incremental concept formation Artificial Intelligence. 40: 11-61. DOI: 10.1016/0004-3702(89)90046-5 |
0.496 |
|
| 1988 |
Langley P. Machine Learning as an Experimental Science Machine Learning. 3: 5-8. DOI: 10.1023/A:1022623814640 |
0.364 |
|
| 1987 |
Langley P. Machine Learning and Concept Formation Machine Learning. 2: 99-102. DOI: 10.1023/A:1022896407371 |
0.368 |
|
| 1987 |
Langley P. Research Papers in Machine Learning Machine Learning. 2: 195-198. DOI: 10.1023/A:1022603230145 |
0.384 |
|
| 1987 |
Langley P. Structure and process in schema-based architectures Behavioral and Brain Sciences. 10: 442. DOI: 10.1017/S0140525X00023426 |
0.304 |
|
| 1987 |
Langley P. Machine learning and grammar induction Machine Learning. 2: 5-8. DOI: 10.1007/Bf00058752 |
0.355 |
|
| 1986 |
Rose D, Langley P. Chemical Discovery as Belief Revision Machine Learning. 1: 423-452. DOI: 10.1023/A:1022870800276 |
0.425 |
|
| 1986 |
Langley P. Editorial: Human and Machine Learning Machine Learning. 1: 243-248. DOI: 10.1023/A:1022854429410 |
0.448 |
|
| 1986 |
Langley P. Editorial: The Terminology of Machine Learning Machine Learning. 1: 141-144. DOI: 10.1023/A:1022840627593 |
0.357 |
|
| 1986 |
Langley P, Michalski RS. Editorial: Machine Learning and Discovery Machine Learning. 1: 363-366. DOI: 10.1023/A:1022814715297 |
0.362 |
|
| 1986 |
Langley P. Editorial: On Machine Learning Machine Learning. 1: 5-10. DOI: 10.1023/A:1022687019898 |
0.356 |
|
| 1986 |
Langley P. Induction and explanation: Complementary models of learning Behavioral and Brain Sciences. 9: 661-662. DOI: 10.1017/S0140525X00051694 |
0.454 |
|
| 1985 |
Langley P. Learning to search: From weak methods to domain-specific heuristics Cognitive Science. 9: 217-260. DOI: 10.1016/S0364-0213(85)80015-X |
0.315 |
|
| 1983 |
Langley P. Exploring the space of cognitive architectures Behavior Research Methods &Amp; Instrumentation. 15: 289-299. DOI: 10.3758/Bf03203563 |
0.35 |
|
| 1983 |
Langley P. Learning search strategies through discrimination International Journal of Man-Machine Studies. 18: 513-541. DOI: 10.1016/S0020-7373(83)80030-3 |
0.404 |
|
| 1982 |
Sleeman DH, Langley P, Mitchell TM. Learning from Solution Paths: An Approach to the Credit Assignment Problem Ai Magazine. 3: 48-52. DOI: 10.1609/Aimag.V3I2.372 |
0.41 |
|
| 1981 |
Langley P. Data-driven discovery of physical laws Cognitive Science. 5: 31-54. DOI: 10.1111/J.1551-6708.1981.Tb00869.X |
0.349 |
|
| 1979 |
Langley P. A production system model for the induction of mathematical functions Behavioral Science. 24: 121-139. DOI: 10.1002/Bs.3830240206 |
0.367 |
|
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