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ORCIDPat Langley
Person information
- affiliation: Institute for the Study of Learning and Expertise, Palo Alto, CA, USA
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Books and Theses
- 1994
[b1]Pat Langley:
Elements of Machine Learning. Morgan Kaufmann 1994, ISBN 1-55860-301-8
Journal Articles
- 2021
- [j56]Pat Langley:
Agents of Exploration and Discovery. AI Mag. 42(4): 72-82 (2021) - 2018
- [j55]Dongkyu Choi
, Pat Langley:
Evolution of the Icarus Cognitive Architecture. Cogn. Syst. Res. 48: 25-38 (2018) - 2017
- [j54]Pat Langley:
Interactive Cognitive Systems and Social Intelligence. IEEE Intell. Syst. 32(4): 22-30 (2017) - 2015
- [j53]Mahmoud Dinar, Andreea Danielescu, Christopher MacLellan, Jami J. Shah, Pat Langley:
Problem Map: An Ontological Framework for a Computational Study of Problem Formulation in Engineering Design. J. Comput. Inf. Sci. Eng. 15(3) (2015) - 2013
- [j52]Christopher J. MacLellan, Pat Langley, Jami Shah, Mahmoud Dinar:
A Computational Aid for Problem Formulation in Early Conceptual Design. J. Comput. Inf. Sci. Eng. 13(3) (2013) - 2012
- [j51]Sam Blisard, Ted Carmichael, Li Ding, Tim Finin, Wende Frost, Arthur C. Graesser, Mirsad Hadzikadic, Lalana Kagal, Geert-Jan M. Kruijff, Pat Langley, James C. Lester, Deborah L. McGuinness, Jack Mostow, Panagiotis Papadakis, Fiora Pirri, Rashmi Prasad, Svetlana Stoyanchev, Pradeep Varakantham:
Reports of the AAAI 2011 Fall Symposia. AI Mag. 33(1): 71-78 (2012) - 2011
- [j50]Pat Langley:
The changing science of machine learning. Mach. Learn. 82(3): 275-279 (2011) - 2010
- [j49]Will Bridewell, Pat Langley:
Two Kinds of Knowledge in Scientific Discovery. Top. Cogn. Sci. 2(1): 36-52 (2010) - 2009
- [j48]Pat Langley, John E. Laird, Seth Rogers:
Cognitive architectures: Research issues and challenges. Cogn. Syst. Res. 10(2): 141-160 (2009) - [j47]Tolga Könik, Paul O'Rorke, Daniel G. Shapiro, Dongkyu Choi, Negin Nejati, Pat Langley:
Skill transfer through goal-driven representation mapping. Cogn. Syst. Res. 10(3): 270-285 (2009) - [j46]Pat Langley, Dongkyu Choi, Seth Rogers:
Acquisition of hierarchical reactive skills in a unified cognitive architecture. Cogn. Syst. Res. 10(4): 316-332 (2009) - 2008
- [j45]Nicholas L. Cassimatis, Paul Bello, Pat Langley:
Ability, Breadth, and Parsimony in Computational Models of Higher-Order Cognition. Cogn. Sci. 32(8): 1304-1322 (2008) - [j44]Will Bridewell, Pat Langley, Ljupco Todorovski, Saso Dzeroski:
Inductive process modeling. Mach. Learn. 71(1): 1-32 (2008) - 2006
- [j43]Pat Langley:
Cognitive Architectures and General Intelligent Systems. AI Mag. 27(2): 33-44 (2006) - [j42]Pat Langley, Oren Shiran, Jeff Shrager, Ljupco Todorovski, Andrew Pohorille:
Constructing explanatory process models from biological data and knowledge. Artif. Intell. Medicine 37(3): 191-201 (2006) - [j41]Will Bridewell, Javier Nicolás Sánchez, Pat Langley, Dorrit Billman:
An interactive environment for the modeling and discovery of scientific knowledge. Int. J. Hum. Comput. Stud. 64(11): 1099-1114 (2006) - [j40]Pat Langley, Dongkyu Choi:
Learning Recursive Control Programs from Problem Solving. J. Mach. Learn. Res. 7: 493-518 (2006) - 2005
- [j39]Randolph M. Jones, Pat Langley:
A Constrained Architecture for Learning and Problem Solving. Comput. Intell. 21(4): 480-502 (2005) - [j38]Ryutaro Ichise, Daniel G. Shapiro, Pat Langley:
Structured program induction from behavioral traces. Syst. Comput. Jpn. 36(11): 49-59 (2005) - 2004
- [j37]Stefan Schrödl, Kiri Wagstaff, Seth Rogers, Pat Langley, Christopher Wilson:
Mining GPS Traces for Map Refinement. Data Min. Knowl. Discov. 9(1): 59-87 (2004) - [j36]Cynthia A. Thompson, Mehmet H. Göker, Pat Langley:
A Personalized System for Conversational Recommendations. J. Artif. Intell. Res. 21: 393-428 (2004) - [j35]Nada Lavrac, Hiroshi Motoda, Tom Fawcett, Robert Holte, Pat Langley, Pieter W. Adriaans:
Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. Mach. Learn. 57(1-2): 13-34 (2004) - 2003
- [j34]Marcus A. Maloof, Pat Langley, Thomas O. Binford, Ramakant Nevatia, Stephanie Sage:
Improved Rooftop Detection in Aerial Images with Machine Learning. Mach. Learn. 53(1-2): 157-191 (2003) - 2002
- [j33]Stephen D. Bay, Jeff Shrager, Andrew Pohorille, Pat Langley:
Revising regulatory networks: from expression data to linear causal models. J. Biomed. Informatics 35(5-6): 289-297 (2002) - 2000
- [j32]Sakir Kocabas, Pat Langley:
Computer generation of process explanations in nuclear astrophysics. Int. J. Hum. Comput. Stud. 53(3): 377-392 (2000) - [j31]Pat Langley:
The computational support of scientific discovery. Int. J. Hum. Comput. Stud. 53(3): 393-410 (2000) - [j30]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. 53(6): 1147-1147 (2000) - [j29]Sakir Kocabas, Pat Langley:
Computer generation of process explanations in nuclear astrophysics. Int. J. Hum. Comput. Stud. 53(6): 1149-1164 (2000) - 1997
- [j28]Avrim Blum, Pat Langley:
Selection of Relevant Features and Examples in Machine Learning. Artif. Intell. 97(1-2): 245-271 (1997) - [j27]Pat Langley, Karl Pfleger, Mehran Sahami:
Lazy Acquisition of Place Knowledge. Artif. Intell. Rev. 11(1-5): 315-342 (1997) - [j26]Brian Yamauchi, Pat Langley:
Place recognition in dynamic environments. J. Field Robotics 14(2): 107-120 (1997) - [j25]Pat Langley, Gregory M. Provan, Padhraic Smyth:
Learning with Probabilistic Representations. Mach. Learn. 29(2-3): 91-101 (1997) - 1996
- [j24]Kevin Knight, Pat Langley, Paul R. Cohen:
What makes a compelling empirical evaluation? IEEE Expert 11(5): 10-14 (1996) - 1995
- [j23]Pat Langley, Herbert A. Simon:
Applications of Machine Learning and Rule Induction. Commun. ACM 38(11): 54-64 (1995) - 1993
- [j22]Bernd Nordhausen, Pat Langley:
An Integrated Framework for Empirical Discovery. Mach. Learn. 12: 17-47 (1993) - 1991
- [j21]Pat Langley, Kathleen B. McKusick, John A. Allen, Wayne Iba, Kevin Thompson:
A Design for the Icarus Architecture. SIGART Bull. 2(4): 104-109 (1991) - 1990
- [j20]Pat Langley:
Advice to Machine Learning Authors. Mach. Learn. 5: 233-237 (1990) - 1989
- [j19]John H. Gennari, Pat Langley, Douglas H. Fisher:
Models of Incremental Concept Formation. Artif. Intell. 40(1-3): 11-61 (1989) - [j18]Pat Langley, Jan M. Zytkow:
Data-Driven Approaches to Empirical Discovery. Artif. Intell. 40(1-3): 283-312 (1989) - [j17]Pat Langley:
Toward a Unified Science of Machine Learning. Mach. Learn. 3: 253-259 (1989) - 1988
- [j16]Pat Langley:
Machine Learning as an Experimental Science. Mach. Learn. 3: 5-8 (1988) - 1987
- [j15]Wayne Iba, Pat Langley:
A computational theory of motor learning. Comput. Intell. 3: 338-350 (1987) - [j14]Pat Langley:
Machine Learning and Grammar Induction. Mach. Learn. 2(1): 5-8 (1987) - [j13]Pat Langley:
Machine Learning and Concept Formation. Mach. Learn. 2(2): 99-102 (1987) - [j12]Pat Langley:
Research Papers in Machine Learning. Mach. Learn. 2(3): 195-198 (1987) - 1986
- [j11]Pat Langley:
On Machine Learning. Mach. Learn. 1(1): 5-10 (1986) - [j10]Pat Langley:
Editorial: The Terminology of Machine Learning. Mach. Learn. 1(2): 141-144 (1986) - [j9]Pat Langley:
Editorial: Human and Machine Learning. Mach. Learn. 1(3): 243-248 (1986) - [j8]Pat Langley, Ryszard S. Michalski:
Machine Learning and Discovery. Mach. Learn. 1(4): 363-366 (1986) - [j7]Donald Rose, Pat Langley:
Chemical Discovery as Belief Revision. Mach. Learn. 1(4): 423-451 (1986) - 1985
- [j6]Pat Langley:
Learning to Search: From Weak Methods to Domain-Specific Heuristics. Cogn. Sci. 9(2): 217-260 (1985) - 1984
- [j5]Pat Langley, Jaime G. Carbonell:
Approaches to machine learning. J. Am. Soc. Inf. Sci. 35(5): 306-316 (1984) - 1983
- [j4]Pat Langley:
Representational Issues in Learning Systems. Computer 16(10): 47-51 (1983) - [j3]Pat Langley:
Learning Search Strategies through Discrimination. Int. J. Man Mach. Stud. 18(6): 513-541 (1983) - 1982
- [j2]Derek H. Sleeman, Pat Langley, Tom M. Mitchell:
Learning from Solution Paths: An Approach to the Credit Assignment Problem. AI Mag. 3(2): 48-52 (1982) - 1981
- [j1]Pat Langley:
Data-Driven Discovery of Physical Laws. Cogn. Sci. 5(1): 31-54 (1981)
Conference and Workshop Papers
- 2024
- [c117]Pat Langley:
Integrated Systems for Computational Scientific Discovery. AAAI 2024: 22598-22606 - 2022
- [c116]Pat Langley:
The Computational Gauntlet of Human-Like Learning. AAAI 2022: 12268-12273 - [c115]Pat Langley, Edward Katz:
Extending an Embodied Cognitive Architecture with Spatial Representation and Reasoning. HLC 2022: 41-45 - [c114]Pat Langley:
Abstract: The Computational Gauntlet of Human-Like Learning 59Pat Langley. HLC 2022: 59 - [c113]Pat Langley:
Representing and Processing Emotions in a Cognitive Architecture. HLC 2022: 60-64 - [c112]Pat Langley:
Learning Hierarchical Problem Networks for Knowledge-Based Planning. ILP 2022: 69-83 - 2020
- [c111]Pat Langley:
Open-World Learning for Radically Autonomous Agents. AAAI 2020: 13539-13543 - 2019
- [c110]Pat Langley:
An Integrative Framework for Artificial Intelligence Education. AAAI 2019: 9670-9677 - [c109]Pat Langley:
Explainable, Normative, and Justified Agency. AAAI 2019: 9775-9779 - 2018
- [c108]Dongkyu Choi, Pat Langley, Son Thanh To:
Creating and Using Tools in a Hybrid Cognitive Architecture. AAAI Spring Symposia 2018 - [c107]Pat Langley, Mohan Sridharan, Ben Meadows:
Representation, Use, and Acquisition of Affordances in Cognitive Systems. AAAI Spring Symposia 2018 - 2017
- [c106]Pat Langley, Adam Arvay:
Flexible Model Induction through Heuristic Process Discovery. AAAI 2017: 4415-4421 - [c105]Pat Langley, Ben Meadows, Mohan Sridharan, Dongkyu Choi:
Explainable Agency for Intelligent Autonomous Systems. AAAI 2017: 4762-4764 - [c104]Pat Langley:
Progress and Challenges in Research on Cognitive Architectures. AAAI 2017: 4870-4876 - [c103]Pat Langley, Richard Cooper:
Symposium on Problem Solving and Goal-Directed Sequential Activity. CogSci 2017 - 2016
- [c102]Pat Langley:
An Architectural Account of Variation in Problem Solving and Execution. CogSci 2016 - 2015
- [c101]Alfredo Gabaldon, Pat Langley:
Dialogue Understanding in a Logic of Action and Belief. AAAI 2015: 515-521 - [c100]Pat Langley, Adam Arvay:
Heuristic Induction of Rate-Based Process Models. AAAI 2015: 537-543 - [c99]Ben Leon Meadows, Richard Heald, Pat Langley:
An Integrated Account of Explanation and Question Answering. CogSci 2015 - 2014
- [c98]Chris Pearce, Ben Leon Meadows, Pat Langley, Mike Barley:
Social Planning: Achieving Goals by Altering Others' Mental States. AAAI 2014: 402-409 - [c97]Alfredo Gabaldon, Pat Langley, Ben Meadows, Ted Selker:
Knowledge-Guided Interpretation and Generation of Task-Oriented Dialogue. IWSDS 2014: 27-39 - 2013
- [c96]Ben Leon Meadows, Pat Langley, Miranda Jane Emery:
Seeing Beyond Shadows: Incremental Abductive Reasoning for Plan Understanding. AAAI Workshop: Plan, Activity, and Intent Recognition 2013 - [c95]Alfredo Gabaldon, Pat Langley, Ben Meadows:
Meta-Level and Domain-Level Processing in Task-Oriented Dialogue. AAAI Fall Symposia 2013 - 2012
- [c94]Ljupco Todorovski, Will Bridewell, Pat Langley:
Discovering Constraints for Inductive Process Modeling. AAAI 2012: 256-262 - [c93]Pat Langley, Glen Hunt:
A Web-Based Environment for Explanatory Biological Modeling. AAAI Fall Symposium: Discovery Informatics 2012 - 2011
- [c92]Nan Li, David J. Stracuzzi, Pat Langley:
Improving Acquisition of Teleoreactive Logic Programs through Representation Change. AAAI Fall Symposium: Advances in Cognitive Systems 2011 - [c91]Nishant Trivedi, Pat Langley, Paul W. Schermerhorn, Matthias Scheutz:
Communicating, Interpreting, and Executing High-Level Instructions for Human-Robot Interaction. AAAI Fall Symposium: Advances in Cognitive Systems 2011 - [c90]Pat Langley, Will Bridewell:
Combining Data-Driven and Knowledge-Guided Methods to Induce Interpretable Physiological Models. AAAI Spring Symposium: Computational Physiology 2011 - [c89]Will Bridewell, Pat Langley:
A Computational Account of Everyday Abductive Inference. CogSci 2011 - [c88]Wayne Iba, Pat Langley:
Exploring Moral Reasoning in a Cognitive Architecture. CogSci 2011 - [c87]Pat Langley, Dongkyu Choi:
Tutorial on the Icarus Cognitive Architecture. CogSci 2011 - 2010
- [c86]Chunki Park, Will Bridewell, Pat Langley:
Integrated Systems for Inducing Spatio-Temporal Process Models. AAAI 2010: 1555-1560 - [c85]Pat Langley, Nishant Trivedi, Matt Banister:
A Command Language for Taskable Virtual Agents. AIIDE 2010 - 2008
- [c84]Art Pope, Pat Langley:
CASTLE: A Framework for Integrating Cognitive Models into Virtual Environments. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures 2008: 152 - 2007
- [c83]Dongkyu Choi, Tolga Könik, Negin Nejati, Chunki Park, Pat Langley:
A Believable Agent for First-Person Shooter Games. AIIDE 2007: 71-73 - 2006
- [c82]Pat Langley, Dongkyu Choi:
A Unified Cognitive Architecture for Physical Agents. AAAI 2006: 1469-1474 - [c81]Will Bridewell, Pat Langley, Steve Racunas, Stuart R. Borrett:
Learning Process Models with Missing Data. ECML 2006: 557-565 - [c80]Nima Asgharbeygi, David J. Stracuzzi, Pat Langley:
Relational temporal difference learning. ICML 2006: 49-56 - [c79]Negin Nejati, Pat Langley, Tolga Könik:
Learning hierarchical task networks by observation. ICML 2006: 665-672 - 2005
- [c78]Ljupco Todorovski, Will Bridewell, Oren Shiran, Pat Langley:
Inducing Hierarchical Process Models in Dynamic Domains. AAAI 2005: 892-897 - [c77]Will Bridewell, Narges Bani Asadi, Pat Langley, Ljupco Todorovski:
Reducing overfitting in process model induction. ICML 2005: 81-88 - [c76]Nima Asgharbeygi, Negin Nejati, Pat Langley, Sachiyo Arai:
Guiding Inference Through Relational Reinforcement Learning. ILP 2005: 20-37 - [c75]Dongkyu Choi, Pat Langley:
Learning Teleoreactive Logic Programs from Problem Solving. ILP 2005: 51-68 - [c74]Pat Langley:
An Adaptive Architecture for Physical Agents. Web Intelligence 2005: 18-25 - 2004
- [c73]Dongkyu Choi, Matthew T. Kaufman, Pat Langley, Negin Nejati, Daniel G. Shapiro:
An Architecture for Persistent Reactive Behavior. AAMAS 2004: 988-995 - 2003
- [c72]Dileep George, Kazumi Saito, Pat Langley, Stephen D. Bay, Kevin R. Arrigo:
Discovering Ecosystem Models from Time-Series Data. Discovery Science 2003: 141-152 - [c71]Pat Langley, Dileep George, Stephen D. Bay, Kazumi Saito:
Robust Induction of Process Models from Time-Series Data. ICML 2003: 432-439 - [c70]Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley:
An adaptive stock tracker for personalized trading advice. IUI 2003: 197-203 - [c69]Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley:
Personalized trading recommendation system. IUI 2003: 332 - [c68]Javier Nicolás Sánchez, Pat Langley:
An interactive environment for scientific model construction. K-CAP 2003: 138-145 - [c67]Lonnie Chrisman, Pat Langley, Stephen D. Bay:
Incorporating Biological Knowledge into Evaluation of Causal Regulatory Hypotheses. Pacific Symposium on Biocomputing 2003: 128-139 - 2002
- [c66]Kazumi Saito, Stephen D. Bay, Pat Langley:
Revising Qualitative Models of Gene Regulation. Discovery Science 2002: 59-70 - [c65]Ryutaro Ichise, Daniel G. Shapiro, Pat Langley:
Learning Hierarchical Skills from Observation. Discovery Science 2002: 247-258 - [c64]Stephen D. Bay, Daniel G. Shapiro, Pat Langley:
Revising Engineering Models: Combining Computational Discovery with Knowledge. ECML 2002: 10-22 - [c63]Pat Langley, Javier Nicolás Sánchez, Ljupco Todorovski, Saso Dzeroski:
Inducing Process Models from Continuous Data. ICML 2002: 347-354 - [c62]Daniel G. Shapiro, Pat Langley:
Separating Skills from Preference: Using Learning to Program by Reward. ICML 2002: 570-577 - [c61]Jeff Shrager, Pat Langley, Andrew Pohorille:
Guiding Revision of Regulatory Models with Expression Data. Pacific Symposium on Biocomputing 2002: 486-497 - [c60]Kazumi Saito, Pat Langley:
Discovering Empirical Laws of Web Dynamics. SAINT 2002: 168-175 - 2001
- [c59]Wayne Iba, Pat Langley:
Unsupervised Learning of Probabilistic Concept Hierarchies. Machine Learning and Its Applications 2001: 39-70 - [c58]Pat Langley:
The Computational Support of Scientific Discovery. Machine Learning and Its Applications 2001: 230-248 - [c57]Daniel G. Shapiro, Pat Langley, Ross D. Shachter:
Using background knowledge to speed reinforcement learning in physical agents. Agents 2001: 254-261 - [c56]Saso Dzeroski, Pat Langley:
Computational Discovery of Communicable Knowledge: Symposium Report. Discovery Science 2001: 45-49 - [c55]Sakir Kocabas, Pat Langley:
An Integrated Framework for Extended Discovery in Particle Physics. Discovery Science 2001: 182-195 - [c54]Kazumi Saito, Pat Langley, Trond Grenager, Christopher Potter, Alicia Torregrosa, Steven A. Klooster:
Computational Revision of Quantitative Scientific Models. Discovery Science 2001: 336-349 - [c53]Mark Schwabacher, Pat Langley:
Discovering Communicable Scientific Knowledge from Spatio-Temporal Data. ICML 2001: 489-496 - [c52]Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoon P. Yoo:
Generalized clustering, supervised learning, and data assignment. KDD 2001: 299-304 - 2000
- [c51]Pat Langley, Sean Stromsten:
Learning Context-Free Grammars with a Simplicity Bias. ECML 2000: 220-228 - [c50]Pat Langley:
Crafting Papers on Machine Learning. ICML 2000: 1207-1216 - 1999
- [c49]Seth Rogers, Claude-Nicolas Fiechter, Pat Langley:
An Adaptive Interactive Agent for Route Advice. Agents 1999: 198-205 - [c48]Daniel G. Shapiro, Pat Langley:
Controlling Physical Agents Through Reactive Logic Programming. Agents 1999: 386-387 - [c47]Pat Langley, Cynthia A. Thompson, Renee Elio, Afsaneh Haddadi:
An Adaptive Conversational Interface for Destination Advice. CIA 1999: 347-364 - [c46]Melinda T. Gervasio, Wayne Iba, Pat Langley:
Learning User Evaluation Functions for Adaptive Scheduling Assistance. ICML 1999: 152-161 - [c45]Pat Langley, Stephanie Sage:
Tractable Average-Case Analysis of Naive Bayesian Classifiers. ICML 1999: 220-228 - [c44]Seth Rogers, Pat Langley, Christopher Wilson:
Mining GPS Data to Augment Road Models. KDD 1999: 104-113 - 1998
- [c43]David E. Moriarty, Pat Langley:
Learning Cooperative Lane Selection Strategies for Highways. AAAI/IAAI 1998: 684-691 - [c42]Melinda T. Gervasio, Wayne Iba, Pat Langley:
Learning to Predict User Operations for Adaptive Scheduling. AAAI/IAAI 1998: 721-726 - [c41]Pat Langley:
The Computer-Aided Discovery of Scientific Knowledge. Discovery Science 1998: 25-39 - [c40]Simon Handley, Pat Langley, Folke A. Rauscher:
Learning to Predict the Duration of an Automobile Trip. KDD 1998: 219-223 - [c39]Marcus A. Maloof, Pat Langley, Thomas O. Binford, Ramakant Nevatia:
Generalizing over aspect and location for rooftop detection. WACV 1998: 194-199 - 1997
- [c38]Pat Langley:
Machine Learning for Intelligent Systems. AAAI/IAAI 1997: 763-769 - [c37]Pat Langley:
Learning to Sense Selectively in Physical Domains. Agents 1997: 217-226 - [c36]Pat Langley:
Machine Learning for Adaptive User Interfaces. KI 1997: 53-62 - 1996
- [c35]Pat Langley:
Induction of Condensed Determinations. KDD 1996: 327-330 - [c34]George H. John, Pat Langley:
Static Versus Dynamic Sampling for Data Mining. KDD 1996: 367-370 - 1995
- [c33]Pat Langley, Karl Pfleger:
Case-Based Acquisition of Place Knowledge. ICML 1995: 344-352 - [c32]George H. John, Pat Langley:
Estimating Continuous Distributions in Bayesian Classifiers. UAI 1995: 338-345 - 1994
- [c31]Pat Langley, Wayne Iba, Jeff Shrager:
Reactive and Automatic Behavior in Plan Execution. AIPS 1994: 299-304 - [c30]Pat Langley, Stephanie Sage:
Induction of Selective Bayesian Classifiers. UAI 1994: 399-406 - 1993
- [c29]Pat Langley:
Induction of Recursive Bayesian Classifiers. ECML 1993: 153-164 - [c28]Pat Langley, Wayne Iba:
Average-Case Analysis of a Nearest Neighbor Algorithm. IJCAI 1993: 889-894 - 1992
- [c27]Pat Langley, Wayne Iba, Kevin Thompson:
An Analysis of Bayesian Classifiers. AAAI 1992: 223-228 - [c26]Wayne Iba, Pat Langley:
Induction of One-Level Decision Trees. ML 1992: 233-240 - 1991
- [c25]Pat Langley, John A. Allen:
The Acquisition of Human Planning Expertise. ML 1991: 80-84 - [c24]Kevin Thompson, Pat Langley, Wayne Iba:
Using Background Knowledge in Concept Formation. ML 1991: 554-558 - [c23]Kathleen B. McKusick, Pat Langley:
Constraints on Tree Structure in Concept Formation. IJCAI 1991: 810-816 - 1990
- [c22]Bernd Nordhausen, Pat Langley:
A Robust Approach to Numeric Discovery. ML 1990: 411-418 - 1989
- [c21]Pat Langley:
Unifying Themes in Empirical and Explanation-Based Learning. ML 1989: 2-4 - [c20]John A. Allen, Pat Langley:
Using Concept Hierarchies to Organize Plan Knowledge. ML 1989: 229-231 - [c19]Kevin Thompson, Pat Langley:
Incremental Concept Formation with Composite Objects. ML 1989: 371-374 - [c18]James Wogulis, Pat Langley:
Improving Efficiency by Learning Intermediate Concepts. IJCAI 1989: 657-662 - 1988
- [c17]Dennis F. Kibler, Pat Langley:
Machine Learning as an Experimental Science. EWSL 1988: 81-92 - [c16]Wayne Iba, James Wogulis, Pat Langley:
Trading Off Simplicity and Coverage in Incremental concept Learning. ML 1988: 73-79 - [c15]Donald Rose, Pat Langley:
A Hill-Climbing Approach to Machine Discovery. ML 1988: 367-373 - 1987
- [c14]Bernd Nordhausen, Pat Langley:
Towards an Integrated Discovery System. IJCAI 1987: 198-200 - 1986
- [c13]Donald Rose, Pat Langley:
STAHLp: Belief Revision in Scientific Discovery. AAAI 1986: 528-532 - 1985
- [c12]Douglas H. Fisher, Pat Langley:
Approaches to Conceptual Clustering. IJCAI 1985: 691-697 - 1984
- [c11]Pat Langley, Stellan Ohlsson:
Automated Cognitive Modeling. AAAI 1984: 193-197 - 1983
- [c10]Stephanie Sage, Pat Langley:
Modeling Cognitive Development on the Balance Scale Task. IJCAI 1983: 94-96 - [c9]Pat Langley:
Learning Effective Search Heuristics. IJCAI 1983: 419-421 - [c8]Pat Langley, Jan M. Zytkow, Gary L. Bradshaw, Herbert A. Simon:
Three Facets of Scientific Discovery. IJCAI 1983: 465-468 - 1982
- [c7]Pat Langley:
A Model of Early Syntactic Development. ACL 1982: 145-151 - [c6]Pat Langley:
Strategy Acquisition Governed by Experimentation. ECAI 1982: 171-176 - 1981
- [c5]Pat Langley, Gary L. Bradshaw, Herbert A. Simon:
BACON.5: The Discovery of Conservation Laws. IJCAI 1981: 121-126 - 1980
- [c4]Pat Langley:
A Production System Model Of First Language Acquisition. COLING 1980: 183-189 - 1979
- [c3]Pat Langley:
Rediscovering Physics with BACON.3. IJCAI 1979: 505-507 - 1977
- [c2]Michael D. Rychener, Charles Forgy, Pat Langley, John P. McDermott, Allen Newell, K. Ramakrishna:
Problems in Building an Instructable Production System. IJCAI 1977: 337 - [c1]Pat Langley:
BACON: A Production System That Discovers Empirical Laws. IJCAI 1977: 344
Parts in Books or Collections
- 2007
- [p3]Saso Dzeroski, Pat Langley, Ljupco Todorovski:
Computational Discovery of Scientific Knowledge. Computational Discovery of Scientific Knowledge 2007: 1-14 - [p2]Kazumi Saito, Pat Langley:
Quantitative Revision of Scientific Models. Computational Discovery of Scientific Knowledge 2007: 120-137 - [p1]Mark Schwabacher, Pat Langley, Christopher Potter, Steven A. Klooster, Alicia Torregrosa:
Discovering Communicable Models from Earth Science Data. Computational Discovery of Scientific Knowledge 2007: 138-157
Editorship
- 2000
- [e1]Pat Langley:
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29 - July 2, 2000. Morgan Kaufmann 2000, ISBN 1-55860-707-2 [contents]
Data and Artifacts
- 1992
- [d1]Pat Langley, Douglas H. Fisher:
Quadruped Mammals. UCI Machine Learning Repository, 1992
Informal and Other Publications
- 2022
- [i4]Christopher J. MacLellan, Peter Matsakis, Pat Langley:
Efficient Induction of Language Models Via Probabilistic Concept Formation. CoRR abs/2212.11937 (2022) - 2013
- [i3]George H. John, Pat Langley:
Estimating Continuous Distributions in Bayesian Classifiers. CoRR abs/1302.4964 (2013) - [i2]Pat Langley, Stephanie Sage:
Induction of Selective Bayesian Classifiers. CoRR abs/1302.6828 (2013) - 2011
- [i1]Mehmet H. Göker, Pat Langley, Cynthia A. Thompson:
A Personalized System for Conversational Recommendations. CoRR abs/1107.0029 (2011)
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