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Pat Langley [FOAF]  [Follow]

Position: Director
Affiliation: Institute for the Study of Learning and Expertise
Address: Institute for the Study of Learning and Expertise 2164 Staunton Court, Palo Alto, CA 94306
Phone: (650) 494-3884
Fax: (650) 494-1588
Email:
Homepage: http://www.isle.org/~langley/
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Statistics: H-index: 25 (See all experts' h-index.)
total citation number: 3076
highest-cited paper: An Analysis of Bayesian Classifiers (1992) at AAAI (Cited By 771)

bio:

Dr. Pat Langley serves as Director of the Institute for the Study of Learning and Expertise, Consult ... More

Research Interest:

Machine Learning, Explanation-Based Learning, Learning Context-Free Grammars, Learning Cooperative Lane Selection, Learning Effective Search Heuristics

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National Science Foundation - US

[9] Computational Approaches to Creativity Through Goal-Directed Cross-Domain Analogy (0738317), 2007-09-15 － 2009-08-31
[8] ITR: Computational Induction of Scientific Process Models (0326059), 2003-09-15 － 2009-08-31
[7] SGER: New Research Directions in Integrated Cognitive Architectures (0335353), 2003-08-01 － 2005-07-31
[6] A Symposium on Learning and Motivation in Cognitive Architectures (0321888), 2003-04-01 － 2004-03-31
[5] Research Planning Workshop on Applications of Reinforcement Learning (9810208), 1998-04-15 － 1998-09-30
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Publications: [Edit disambiguation Result]

2008(1)
[127]Will Bridewell, Pat Langley, Ljupco Todorovski, Saso Dzeroski. Inductive process modeling. Machine Learning, 2008: 1~32    Cited By 21[Bibtex]
2007(4)
[126]Kazumi Saito, Pat Langley. Quantitative Revision of Scientific Models.  Computational Discovery of Scientific Knowledge'2007. pp.120~137   [Bibtex]
[125]Saso Dzeroski, Pat Langley, Ljupco Todorovski. Computational Discovery of Scientific Knowledge.  Computational Discovery of Scientific Knowledge'2007. pp.1~14    Cited By 2[Bibtex]
[124]Mark Schwabacher, Pat Langley, Christopher Potter, Steven A. Klooster, Alicia Torregrosa. Discovering Communicable Models from Earth Science Data.  Computational Discovery of Scientific Knowledge'2007. pp.138~157   [Bibtex]
[123]Dongkyu Choi, Tolga Konik, Negin Nejati, Chunki Park, Pat Langley. A Believable Agent for First-Person Shooter Games.  AIIDE'2007. pp.71~73    Cited By 6[Bibtex]
2006(8)
[122]Pat Langley, Dongkyu Choi. A Unified Cognitive Architecture for Physical Agents.  AAAI'2006.     Cited By 44[Bibtex] [PDF]
[121]Will Bridewell, Pat Langley, Steve Racunas, Stuart R. Borrett. Learning Process Models with Missing Data.  ECML'2006. pp.557~565    Cited By 4[Bibtex]
[120]Nima Asgharbeygi, David J. Stracuzzi, Pat Langley. Relational temporal difference learning.  ICML'2006. pp.49~56    Cited By 11[Bibtex] [PDF]
[119]Negin Nejati, Pat Langley, Tolga Konik. Learning hierarchical task networks by observation.  ICML'2006. pp.665~672    Cited By 41[Bibtex] [PDF]
[118]Pat Langley. Cognitive Architectures and General Intelligent Systems. AI Magazine, 2006: 33~44    Cited By 35[Bibtex]
[117]Pat Langley, Oren Shiran, Jeff Shrager, Ljupco Todorovski, Andrew Pohorille. Constructing explanatory process models from biological data and knowledge. Artificial Intelligence in Medicine, 2006: 191~201    Cited By 16[Bibtex]
[116]Will Bridewell, Javier Nicolas Sanchez, Pat Langley, Dorrit Billman. An interactive environment for the modeling and discovery of scientific knowledge. International Journal of Man-Machine Studies, 2006: 1099~1114    Cited By 16[Bibtex]
[115]Pat Langley, Dongkyu Choi. Learning Recursive Control Programs from Problem Solving. Journal of Machine Learning Research, 2006: 493~518    Cited By 32[Bibtex]
2005(7)
[114]Ljupco Todorovski, Will Bridewell, Oren Shiran, Pat Langley. Inducing Hierarchical Process Models in Dynamic Domains.  AAAI'2005. pp.892~897    Cited By 18[Bibtex]
[113]Randolph M. Jones, Pat Langley. A Constrained Architecture for Learning and Problem Solving. Computational Intelligence, 2005: 480~502    Cited By 11[Bibtex]
[112]Will Bridewell, Narges Bani Asadi, Pat Langley, Ljupco Todorovski. Reducing overfitting in process model induction.  ICML'2005. pp.81~88    Cited By 7[Bibtex] [PDF]
[111]Nima Asgharbeygi, Negin Nejati, Pat Langley, Sachiyo Arai. Guiding Inference Through Relational Reinforcement Learning.  ILP'2005. pp.20~37    Cited By 10[Bibtex] [PDF]
[110]Dongkyu Choi, Pat Langley. Learning Teleoreactive Logic Programs from Problem Solving.  ILP'2005. pp.51~68    Cited By 18[Bibtex] [PDF]
[109]Pat Langley. An Adaptive Architecture for Physical Agents.  Web Intelligence'2005. pp.18~25    Cited By 17[Bibtex]
[108]Ryutaro Ichise, Daniel G. Shapiro, Pat Langley. Structured program induction from behavioral traces. Systems and Computers in Japan, 2005: 49~59   [Bibtex]
2004(4)
[107]Dongkyu Choi, Matt Kaufman, Pat Langley, Negin Nejati, Daniel G. Shapiro. An Architecture for Persistent Reactive Behavior.  AAMAS'2004. pp.988~995    Cited By 32[Bibtex] [PDF]
[106]Stefan Schrodl, Kiri Wagstaff, Seth Rogers, Pat Langley, Christopher Wilson. Mining GPS Traces for Map Refinement. Data Min. Knowl. Discov., 2004: 59~87    Cited By 23[Bibtex]
[105]Cynthia A. Thompson, Mehmet H. Goker, Pat Langley. A Personalized System for Conversational Recommendations. J. Artif. Intell. Res. (JAIR), 2004: 393~428    Cited By 86[Bibtex] [PDF]
[104]Nada Lavrac, Hiroshi Motoda, Tom Fawcett, Robert Holte, Pat Langley, Pieter W. Adriaans. Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. Machine Learning, 2004: 13~34    Cited By 22[Bibtex]
2003(7)
[103]Dileep George, Kazumi Saito, Pat Langley, Stephen D. Bay, Kevin R. Arrigo. Discovering Ecosystem Models from Time-Series Data.  Discovery Science'2003. pp.141~152    Cited By 3[Bibtex] [PDF]
[102]Pat Langley, Dileep George, Stephen D. Bay, Kazumi Saito. Robust Induction of Process Models from Time-Series Data.  ICML'2003. pp.432~439    Cited By 21[Bibtex] [PDF]
[101]Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley. An adaptive stock tracker for personalized trading advice.  IUI'2003. pp.197~203    Cited By 12[Bibtex] [PDF]
[100]Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley. Personalized trading recommendation system.  IUI'2003. pp.332~332   [Bibtex] [PDF]
[99]Javier Nicolas Sanchez, Pat Langley. An interactive environment for scientific model construction.  K-CAP'2003. pp.138~145    Cited By 8[Bibtex] [PDF]
[98]Lonnie Chrisman, Pat Langley, Stephen D. Bay. Incorporating Biological Knowledge into Evaluation of Causal Regulatory Hypotheses.  Pacific Symposium on Biocomputing'2003. pp.128~139    Cited By 16[Bibtex] [PDF]
[97]Marcus A. Maloof, Pat Langley, Thomas O. Binford, Ramakant Nevatia, Stephanie Sage. Improved Rooftop Detection in Aerial Images with Machine Learning. Machine Learning, 2003: 157~191    Cited By 44[Bibtex] [PDF]
2002(8)
[96]Ryutaro Ichise, Daniel G. Shapiro, Pat Langley. Learning Hierarchical Skills from Observation.  Discovery Science'2002. pp.247~258    Cited By 6[Bibtex] [PDF]
[95]Kazumi Saito, Stephen D. Bay, Pat Langley. Revising Qualitative Models of Gene Regulation.  Discovery Science'2002. pp.59~70    Cited By 1[Bibtex] [PDF]
[94]Stephen D. Bay, Daniel G. Shapiro, Pat Langley. Revising Engineering Models: Combining Computational Discovery with Knowledge.  ECML'2002. pp.10~22    Cited By 11[Bibtex]
[93]Pat Langley, Javier Nicolas Sanchez, Ljupco Todorovski, Saso Dzeroski. Inducing Process Models from Continuous Data.  ICML'2002. pp.347~354    Cited By 38[Bibtex] [PDF]
[92]Daniel G. Shapiro, Pat Langley. Separating Skills from Preference: Using Learning to Program by Reward.  ICML'2002. pp.570~577    Cited By 18[Bibtex] [PDF]
[91]Jeff Shrager, Pat Langley, Andrew Pohorille. Guiding Revision of Regulatory Models with Expression Data.  Pacific Symposium on Biocomputing'2002. pp.486~497    Cited By 26[Bibtex] [PDF]
[90]Kazumi Saito, Pat Langley. Discovering Empirical Laws of Web Dynamics.  SAINT'2002. pp.168~175    Cited By 2[Bibtex]
[89]Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pat Langley. Revising regulatory networks: from expression data to linear causal models. Journal of Biomedical Informatics, 2002: 289~297    Cited By 23[Bibtex] [PDF]
2001(8)
[88]Wayne Iba, Pat Langley. Unsupervised Learning of Probabilistic Concept Hierarchies.  Machine Learning and Its Applications'2001. pp.39~70    Cited By 21[Bibtex] [PDF]
[87]Pat Langley. The Computational Support of Scientific Discovery.  Machine Learning and Its Applications'2001. pp.230~248    Cited By 83[Bibtex]
[86]Daniel G. Shapiro, Pat Langley, Ross D. Shachter. Using background knowledge to speed reinforcement learning in physical agents.  Agents'2001. pp.254~261    Cited By 29[Bibtex]
[85]Saso Dzeroski, Pat Langley. Computational Discovery of Communicable Knowledge: Symposium Report.  Discovery Science'2001. pp.45~49    Cited By 1[Bibtex] [PDF]
[84]Kazumi Saito, Pat Langley, Trond Grenager, Christopher Potter, Alicia Torregrosa, Steven A. Klooster. Computational Revision of Quantitative Scientific Models.  Discovery Science'2001. pp.336~349    Cited By 18[Bibtex] [PDF]
[83]Sakir Kocabas, Pat Langley. An Integrated Framework for Extended Discovery in Particle Physics.  Discovery Science'2001. pp.182~195    Cited By 4[Bibtex] [PDF]
[82]Mark Schwabacher, Pat Langley. Discovering Communicable Scientific Knowledge from Spatio-Temporal Data.  ICML'2001. pp.489~496    Cited By 14[Bibtex] [PDF]
[81]Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoon P. Yoo. Generalized clustering, supervised learning, and data assignment.  KDD'2001. pp.299~304    Cited By 28[Bibtex] [PDF]
2000(6)
[80]Pat Langley, Sean Stromsten. Learning Context-Free Grammars with a Simplicity Bias.  ECML'2000. pp.220~228    Cited By 62[Bibtex]
[79]Pat Langley. Crafting Papers on Machine Learning.  ICML'2000. pp.1207~1216    Cited By 16[Bibtex] [PDF]
[78]Sakir Kocabas, Pat Langley. Collaboration, Cooperation and Conflict in Dialogue Systems: Int. J. Human-Computer Studies (2000) 53, 377-392. Int. J. Hum.-Comput. Stud., 2000: 1147~1147   [Bibtex]
[77]Sakir Kocabas, Pat Langley. Computer generation of process explanations in nuclear astrophysics. Int. J. Hum.-Comput. Stud., 2000: 1149~1164    Cited By 2[Bibtex] [PDF]
[76]Sakir Kocabas, Pat Langley. Computer generation of process explanations in nuclear astrophysics. Int. J. Hum.-Comput. Stud., 2000: 377~392    Cited By 2[Bibtex] [PDF]
[75]Pat Langley. The computational support of scientific discovery. Int. J. Hum.-Comput. Stud., 2000: 393~410    Cited By 83[Bibtex]
1999(6)
[74]Seth Rogers, Claude-Nicolas Fiechter, Pat Langley. An Adaptive Interactive Agent for Route Advice.  Agents'1999. pp.198~205    Cited By 88[Bibtex] [PDF]
[73]Daniel G. Shapiro, Pat Langley. Controlling Physical Agents Through Reactive Logic Programming.  Agents'1999. pp.386~387    Cited By 20[Bibtex] [PDF]
[72]Pat Langley, Cynthia A. Thompson, Renee Elio, Afsaneh Haddadi. An Adaptive Conversational Interface for Destination Advice.  CIA'1999. pp.347~364    Cited By 20[Bibtex] [PDF]
[71]Melinda T. Gervasio, Wayne Iba, Pat Langley. Learning User Evaluation Functions for Adaptive Scheduling Assistance.  ICML'1999. pp.152~161    Cited By 23[Bibtex] [PDF]
[70]Pat Langley, Stephanie Sage. Tractable Average-Case Analysis of Naive Bayesian Classifiers.  ICML'1999. pp.220~228    Cited By 23[Bibtex] [PDF]
[69]Seth Rogers, Pat Langley, Christopher Wilson. Mining GPS Data to Augment Road Models.  KDD'1999. pp.104~113    Cited By 32[Bibtex] [PDF]
1998(4)
[68]Melinda T. Gervasio, Wayne Iba, Pat Langley. Learning to Predict User Operations for Adaptive Scheduling.  AAAI/IAAI'1998. pp.721~726    Cited By 15[Bibtex] [PDF]
[67]David E. Moriarty, Pat Langley. Learning Cooperative Lane Selection Strategies for Highways.  AAAI/IAAI'1998. pp.684~691    Cited By 31[Bibtex] [PDF]
[66]Pat Langley. The Computer-Aided Discovery of Scientific Knowledge.  Discovery Science'1998. pp.25~39    Cited By 68[Bibtex] [PDF]
[65]Simon Handley, Pat Langley, Folke A. Rauscher. Learning to Predict the Duration of an Automobile Trip.  KDD'1998. pp.219~223    Cited By 23[Bibtex] [PDF]
1997(6)
[64]Pat Langley. Machine Learning for Intelligent Systems.  AAAI/IAAI'1997. pp.763~769    Cited By 6[Bibtex]
[63]Pat Langley. Learning to Sense Selectively in Physical Domains.  Agents'1997. pp.217~226    Cited By 3[Bibtex]
[62]Pat Langley. Machine Learning for Adaptive User Interfaces.  KI'1997. pp.53~62    Cited By 63[Bibtex] [PDF]
[61]Avrim Blum, Pat Langley. Selection of Relevant Features and Examples in Machine Learning. Artif. Intell., 1997: 245~271    Cited By 1241[Bibtex]
[60]Pat Langley, Karl Pfleger, Mehran Sahami. Lazy Acquisition of Place Knowledge. Artif. Intell. Rev., 1997: 315~342    Cited By 10[Bibtex] [PDF]
[59]Pat Langley, Gregory M. Provan, Padhraic Smyth. Learning with Probabilistic Representations. Machine Learning, 1997: 91~101    Cited By 7[Bibtex]
1996(3)
[58]George H. John, Pat Langley. Static Versus Dynamic Sampling for Data Mining.  KDD'1996. pp.367~370    Cited By 137[Bibtex] [PDF]
[57]Pat Langley. Induction of Condensed Determinations.  KDD'1996. pp.327~330    Cited By 19[Bibtex] [PDF]
[56]Kevin Knight, Pat Langley, Paul R. Cohen. What makes a compelling empirical evaluation?. IEEE Expert, 1996: 10~14   [Bibtex]
1995(3)
[55]Pat Langley, Karl Pfleger. Case-Based Acquisition of Place Knowledge.  ICML'1995. pp.344~352   [Bibtex] [PDF]
[54]George H. John, Pat Langley. Estimating Continuous Distributions in Bayesian Classifiers.  UAI'1995. pp.338~345    Cited By 624[Bibtex]
[53]Pat Langley, Herbert A. Simon. Applications of Machine Learning and Rule Induction. Commun. ACM, 1995: 54~64    Cited By 261[Bibtex] [PDF]
1994(5)
[52]Pat Langley. Elements of Machine Learning. 1994.     Cited By 497[Bibtex]
[51]Pat Langley. Elements of Machine Learning. 1994.     Cited By 497[Bibtex]
[50]Pat Langley. Elements of Machine Learning. 1994.     Cited By 497[Bibtex]
[49]Pat Langley, Wayne Iba, Jeff Shrager. Reactive and Automatic Behavior in Plan Execution.  AIPS'1994. pp.299~304    Cited By 8[Bibtex] [PDF]
[48]Pat Langley, Stephanie Sage. Induction of Selective Bayesian Classifiers.  UAI'1994. pp.399~406    Cited By 466[Bibtex] [PDF]
1993(3)
[47]Pat Langley. Induction of Recursive Bayesian Classifiers.  ECML'1993. pp.153~164    Cited By 89[Bibtex]
[46]Pat Langley, Wayne Iba. Average-Case Analysis of a Nearest Neighbor Algorithm.  IJCAI'1993. pp.889~894    Cited By 94[Bibtex] [PDF]
[45]Bernd Nordhausen, Pat Langley. An Integrated Framework for Empirical Discovery. Machine Learning, 1993: 17~47    Cited By 52[Bibtex]
1992(2)
[44]Pat Langley, Wayne Iba, Kevin Thompson. An Analysis of Bayesian Classifiers.  AAAI'1992. pp.223~228    Cited By 771[Bibtex]
[43]Wayne Iba, Pat Langley. Induction of One-Level Decision Trees.  ML'1992. pp.233~240    Cited By 82[Bibtex] [PDF]
1991(4)
[42]Pat Langley, John A. Allen. The Acquisition of Human Planning Expertise.  ML'1991. pp.80~84    Cited By 11[Bibtex] [PDF]
[41]Kevin Thompson, Pat Langley, Wayne Iba. Using Background Knowledge in Concept Formation.  ML'1991. pp.554~558    Cited By 25[Bibtex] [PDF]
[40]Kathleen B. McKusick, Pat Langley. Constraints on Tree Structure in Concept Formation.  IJCAI'1991. pp.810~816    Cited By 44[Bibtex]
[39]Pat Langley, Kathleen B. McKusick, John A. Allen, Wayne Iba, Kevin Thompson. A Design for the Icarus Architecture. SIGART Bulletin, 1991: 104~109    Cited By 29[Bibtex] [PDF]
1990(2)
[38]Bernd Nordhausen, Pat Langley. A Robust Approach to Numeric Discovery.  ML'1990. pp.411~418    Cited By 17[Bibtex] [PDF]
[37]Pat Langley. Advice to Machine Learning Authors. Machine Learning, 1990: 233~237   [Bibtex]
1989(7)
[36]John A. Allen, Pat Langley. Using Concept Hierarchies to Organize Plan Knowledge.  ML'1989. pp.229~231    Cited By 4[Bibtex] [PDF]
[35]Kevin Thompson, Pat Langley. Incremental Concept Formation with Composite Objects.  ML'1989. pp.371~374    Cited By 26[Bibtex] [PDF]
[34]Pat Langley. Unifying Themes in Empirical and Explanation-Based Learning.  ML'1989. pp.2~4    Cited By 6[Bibtex] [PDF]
[33]James Wogulis, Pat Langley. Improving Efficiency by Learning Intermediate Concepts.  IJCAI'1989. pp.657~662    Cited By 30[Bibtex] [PDF]
[32]John H. Gennari, Pat Langley, Douglas H. Fisher. Models of Incremental Concept Formation. Artif. Intell., 1989: 11~61    Cited By 521[Bibtex]
[31]Pat Langley, Jan M. Zytkow. Data-Driven Approaches to Empirical Discovery. Artif. Intell., 1989: 283~312    Cited By 56[Bibtex]
[30]Pat Langley. Toward a Unified Science of Machine Learning. Machine Learning, 1989: 253~259    Cited By 10[Bibtex]
1988(4)
[29]Dennis F. Kibler, Pat Langley. Machine Learning as an Experimental Science.  EWSL'1988. pp.81~92    Cited By 94[Bibtex]
[28]Wayne Iba, James Wogulis, Pat Langley. Trading Off Simplicity and Coverage in Incremental concept Learning.  ML'1988. pp.73~79    Cited By 84[Bibtex] [PDF]
[27]Donald Rose, Pat Langley. A Hill-Climbing Approach to Machine Discovery.  ML'1988. pp.367~373    Cited By 11[Bibtex] [PDF]
[26]Pat Langley. Machine Learning as an Experimental Science. Machine Learning, 1988: 5~8    Cited By 21[Bibtex]
1987(5)
[25]Wayne Iba, Pat Langley. A computational theory of motor learning. Computational Intelligence, 1987: 338~350    Cited By 4[Bibtex]
[24]Bernd Nordhausen, Pat Langley. Towards an Integrated Discovery System.  IJCAI'1987. pp.198~200    Cited By 12[Bibtex]
[23]Pat Langley. Machine Learning and Concept Formation. Machine Learning, 1987: 99~102    Cited By 20[Bibtex]
[22]Pat Langley. Research Papers in Machine Learning. Machine Learning, 1987: 195~198    Cited By 4[Bibtex]
[21]Pat Langley. Machine Learning and Grammar Induction. Machine Learning, 1987: 5~8    Cited By 12[Bibtex]
1986(6)
[20]Donald Rose, Pat Langley. STAHLp: Belief Revision in Scientific Discovery.  AAAI'1986. pp.528~532    Cited By 7[Bibtex]
[19]Pat Langley, Ryszard S. Michalski. Machine Learning and Discovery. Machine Learning, 1986: 363~366   [Bibtex]
[18]Pat Langley. Editorial: Human and Machine Learning. Machine Learning, 1986: 243~248   [Bibtex]
[17]Pat Langley. Editorial: The Terminology of Machine Learning. Machine Learning, 1986: 141~144    Cited By 7[Bibtex]
[16]Donald Rose, Pat Langley. Chemical Discovery as Belief Revision. Machine Learning, 1986: 423~451    Cited By 44[Bibtex]
[15]Pat Langley. On Machine Learning. Machine Learning, 1986: 5~10   [Bibtex]
1985(2)
[14]Douglas H. Fisher, Pat Langley. Approaches to Conceptual Clustering.  IJCAI'1985. pp.691~697    Cited By 103[Bibtex]
[13]Pat Langley. Learning to Search: From Weak Methods to Domain-Specific Heuristics. Cognitive Science, 1985: 217~260    Cited By 94[Bibtex]
1984(1)
[12]Pat Langley, Stellan Ohlsson. Automated Cognitive Modeling.  AAAI'1984. pp.193~197    Cited By 87[Bibtex]
1983(5)
[11]Pat Langley, Jan M. Zytkow, Gary L. Bradshaw, Herbert A. Simon. Three Facets of Scientific Discovery.  IJCAI'1983. pp.465~468   [Bibtex]
[10]Stephanie Sage, Pat Langley. Modeling Cognitive Development on the Balance Scale Task.  IJCAI'1983. pp.94~96    Cited By 11[Bibtex]
[9]Pat Langley. Learning Effective Search Heuristics.  IJCAI'1983. pp.419~421    Cited By 50[Bibtex] [PDF]
[8]Pat Langley. Representational Issues in Learning Systems. IEEE Computer, 1983: 47~51    Cited By 2[Bibtex]
[7]Pat Langley. Learning Search Strategies through Discrimination. International Journal of Man-Machine Studies, 1983: 513~541    Cited By 21[Bibtex]
1982(2)
[6]Pat Langley. Strategy Acquisition Governed by Experimentation.  ECAI'1982. pp.171~176    Cited By 21[Bibtex]
[5]Derek H. Sleeman, Pat Langley, Tom M. Mitchell. Learning from Solution Paths: An Approach to the Credit Assignment Problem. AI Magazine, 1982: 48~52    Cited By 42[Bibtex]
1981(1)
[4]Pat Langley, Gary L. Bradshaw, Herbert A. Simon. BACON.5: The Discovery of Conservation Laws.  IJCAI'1981. pp.121~126   [Bibtex]
1980(1)
[3]Pat Langley. A Production System Model Of First Language Acquisition.  COLING'1980. pp.183~189    Cited By 8[Bibtex] [PDF]
1977(2)
[2]Pat Langley. BACON: A Production System That Discovers Empirical Laws.  IJCAI'1977. pp.344~344    Cited By 7[Bibtex]
[1]Michael D. Rychener, Charles Forgy, Pat Langley, John P. McDermott, Allen Newell, K. Ramakrishna. Problems in Building an Instructable Production System.  IJCAI'1977. pp.337~337   [Bibtex]