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John E. Laird
John Edwin Laird
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- affiliation: University of Michigan, Ann Arbor, USA
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2020 – today
- 2024
- [c79]James R. Kirk, Robert E. Wray, Peter Lindes, John E. Laird:
Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis. AAAI 2024: 18390-18398 - [c78]Shiwali Mohan, John E. Laird:
Learning Fast and Slow: A Redux of Levels of Learning in General Autonomous Intelligent Agents. AAAI Spring Symposia 2024: 570-571 - [i13]Robert E. Wray, James R. Kirk, John E. Laird:
Eliciting Problem Specifications via Large Language Models. CoRR abs/2405.12147 (2024) - 2023
- [j42]Steven J. Jones, John E. Laird:
A cognitive architecture theory of anticipatory thinking. AI Mag. 44(2): 155-164 (2023) - [c77]Robert E. Wray, Steven J. Jones, John E. Laird:
Computational-Level Analysis of Constraint Compliance for General Intelligence. AGI 2023: 317-327 - [i12]Robert E. Wray, Steven J. Jones, John E. Laird:
Computational-level Analysis of Constraint Compliance for General Intelligence. CoRR abs/2303.04352 (2023) - [i11]James R. Kirk, Robert E. Wray, John E. Laird:
Exploiting Language Models as a Source of Knowledge for Cognitive Agents. CoRR abs/2310.06846 (2023) - 2022
- [j41]Jule Schatz, Steven J. Jones, John E. Laird:
Modeling the Remote Associates Test as Retrievals from Semantic Memory. Cogn. Sci. 46(6) (2022) - [c76]Aaron Mininger, John E. Laird:
A Demonstration of Compositional, Hierarchical Interactive Task Learning. AAAI 2022: 13203-13205 - [i10]John E. Laird:
An Analysis and Comparison of ACT-R and Soar. CoRR abs/2201.09305 (2022) - [i9]John E. Laird:
Introduction to Soar. CoRR abs/2205.03854 (2022) - [i8]James R. Kirk, Robert E. Wray, Peter Lindes, John E. Laird:
Evaluating Diverse Knowledge Sources for Online One-shot Learning of Novel Tasks. CoRR abs/2208.09554 (2022) - [i7]James R. Kirk, Robert E. Wray, Peter Lindes, John E. Laird:
Improving Language Model Prompting in Support of Semi-autonomous Task Learning. CoRR abs/2209.07636 (2022) - 2021
- [j40]Andrea Stocco, Catherine Sibert, Zoe Steine-Hanson, Natalie Koh, John E. Laird, Christian Lebiere, Paul S. Rosenbloom:
Analysis of the human connectome data supports the notion of a "Common Model of Cognition" for human and human-like intelligence across domains. NeuroImage 235: 118035 (2021) - [c75]Catherine Sibert, Holly Sue Hake, John E. Laird, Christian Lebiere, Paul S. Rosenbloom, Andrea Stocco:
The Role of The Basal Ganglia in the Human Cognitive Architecture: A Dynamic Causal Modeling Comparison Across Tasks and Individuals. CogSci 2021 - [i6]Robert E. Wray III, James R. Kirk, John E. Laird:
Language Models as a Knowledge Source for Cognitive Agents. CoRR abs/2109.08270 (2021) - 2020
- [j39]Dagmar Monett, Colin W. P. Lewis, Kristinn R. Thórisson, Joscha Bach, Gianluca Baldassarre, Giovanni Granato, Istvan S. N. Berkeley, François Chollet, Matthew Crosby, Henry Shevlin, John F. Sowa, John E. Laird, Shane Legg, Peter Lindes, Tomás Mikolov, William J. Rapaport, Raúl Rojas, Marek Rosa, Peter Stone, Richard S. Sutton, Roman V. Yampolskiy, Pei Wang, Roger C. Schank, Aaron Sloman, Alan F. T. Winfield:
Special Issue "On Defining Artificial Intelligence" - Commentaries and Author's Response. J. Artif. Gen. Intell. 11(2): 1-100 (2020)
2010 – 2019
- 2019
- [j38]Aaron Adler, Prithviraj Dasgupta, Nick DePalma, Mohammed Eslami, Richard G. Freedman, John E. Laird, Christian Lebiere, Katrin S. Lohan, Ross Mead, Mark Roberts, Paul S. Rosenbloom, Emmanuel Senft, Frank Stein, Tom Williams, Kyle Hollins Wray, Fusun Yaman, Shlomo Zilberstein:
Reports of the 2018 AAAI Fall Symposium. AI Mag. 40(2): 66-72 (2019) - [c74]Steven J. Jones, John E. Laird:
Anticipatory Thinking in Cognitive Architectures with Event Cognition Mechanisms. COGSAT@AAAI Fall Symposium 2019 - [c73]Kenneth D. Forbus, Dedre Gentner, John E. Laird, Thomas R. Shultz, Ardavan Salehi Nobandegani, Paul Thagard:
How Does Current AI Stack Up Against Human Intelligence? CogSci 2019: 27-28 - [c72]James R. Kirk, John E. Laird:
Learning Hierarchical Symbolic Representations to Support Interactive Task Learning and Knowledge Transfer. IJCAI 2019: 6095-6102 - 2018
- [j37]Arjuna Flenner, Marlena R. Fraune, Laura M. Hiatt, Tony Kendall, John E. Laird, Christian Lebiere, Paul S. Rosenbloom, Frank Stein, Elin Anna Topp, Vaibhav V. Unhelkar, Ying Zhao:
Reports of the AAAI 2017 Fall Symposium Series. AI Mag. 39(2): 81-86 (2018) - [c71]Aaron Mininger, John E. Laird:
Interactively Learning a Blend of Goal-Based and Procedural Tasks. AAAI 2018: 1487-1494 - [c70]John E. Laird, Shiwali Mohan:
Learning Fast and Slow: Levels of Learning in General Autonomous Intelligent Agents. AAAI 2018: 7983-7987 - [c69]Andrea Stocco, John E. Laird, Christian Lebiere, Paul S. Rosenbloom:
Empirical Evidence from Neuroimaging Data for a Standard Model of the Mind. CogSci 2018 - 2017
- [j36]John E. Laird, Christian Lebiere, Paul S. Rosenbloom:
A Standard Model of the Mind: Toward a Common Computational Framework across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics. AI Mag. 38(4): 13-26 (2017) - [j35]John E. Laird, Kevin A. Gluck, John R. Anderson, Kenneth D. Forbus, Odest Chadwicke Jenkins, Christian Lebiere, Dario D. Salvucci, Matthias Scheutz, Andrea Thomaz, J. Gregory Trafton, Robert E. Wray, Shiwali Mohan, James R. Kirk:
Interactive Task Learning. IEEE Intell. Syst. 32(4): 6-21 (2017) - [c68]Peter Lindes, John E. Laird:
Cognitive Modeling Approaches to Language Comprehension Using Construction Grammar. AAAI Spring Symposia 2017 - [c67]Peter Lindes, Aaron Mininger, James R. Kirk, John E. Laird:
Grounding Language for Interactive Task Learning. RoboNLP@ACL 2017: 1-9 - 2016
- [c66]James R. Kirk, Aaron Mininger, John E. Laird:
A Demonstration of Interactive Task Learning. IJCAI 2016: 4248-4249 - [i5]Shiwali Mohan, Aaron Mininger, John E. Laird:
Towards an Indexical Model of Situated Language Comprehension for Cognitive Agents in Physical Worlds. CoRR abs/1604.02509 (2016) - [i4]Shiwali Mohan, James R. Kirk, John E. Laird:
A Computational Model for Situated Task Learning with Interactive Instruction. CoRR abs/1604.06849 (2016) - 2015
- [c65]Justin Li, John E. Laird:
Spontaneous Retrieval from Long-Term Memory for a Cognitive Architecture. AAAI 2015: 544-550 - [c64]Shiwali Mohan, James Roberts Kirk, Aaron Mininger, John E. Laird:
Agent Requirements for Effective and Efficient Task-Oriented Dialog. AAAI Fall Symposia 2015: 94-99 - 2014
- [c63]Shiwali Mohan, John E. Laird:
Learning Goal-Oriented Hierarchical Tasks from Situated Interactive Instruction. AAAI 2014: 387-394 - 2013
- [j34]Nate Derbinsky, John E. Laird:
Effective and efficient forgetting of learned knowledge in Soar's working and procedural memories. Cogn. Syst. Res. 24: 104-113 (2013) - [c62]Joseph Zhen Ying Xu, John E. Laird:
Learning Integrated Symbolic and Continuous Action Models for Continuous Domains. AAAI 2013: 991-997 - [c61]Justin Li, John E. Laird:
Preemptive Strategies for Overcoming the Forgetting of Goals. AAAI 2013: 1234-1240 - [c60]John Edwin Laird:
Reflections on Abstractions for General Artificial Intelligence. AAAI Fall Symposia 2013 - [c59]John Edwin Laird, Shiwali Mohan:
A Case Study of Knowledge Integration Across Multiple Memories in Soar. AAAI Fall Symposia 2013 - 2012
- [j33]Andrew M. Nuxoll, John E. Laird:
Enhancing intelligent agents with episodic memory. Cogn. Syst. Res. 17-18: 34-48 (2012) - [c58]Nate Derbinsky, Justin Li, John E. Laird:
A Multi-Domain Evaluation of Scaling in a General Episodic Memory. AAAI 2012: 193-199 - [c57]John Edwin Laird, Keegan R. Kinkade, Shiwali Mohan, Joseph Z. Xu:
Cognitive Robotics Using the Soar Cognitive Architecture. CogRob@AAAI 2012 - [c56]Justin Li, Nate Derbinsky, John E. Laird:
Functional Interactions Between Memory and Recognition Judgments. AAAI 2012: 228-234 - [c55]Shiwali Mohan, John E. Laird:
Exploring Mixed-Initiative Interaction for Learning with Situated Instruction in Cognitive Agents. AAAI 2012: 2445-2446 - [c54]Shiwali Mohan, Aaron Mininger, James R. Kirk, John E. Laird:
Learning Grounded Language through Situated Interactive Instruction. AAAI Fall Symposium: Robots Learning Interactively from Human Teachers 2012 - [c53]Nate Derbinsky, Justin Li, John E. Laird:
Algorithms for scaling in a general episodic memory. AAMAS 2012: 1387-1388 - [i3]Shiwali Mohan, John E. Laird:
Relational Reinforcement Learning in Infinite Mario. CoRR abs/1202.6386 (2012) - 2011
- [j32]Nicholas A. Gorski, John E. Laird:
Learning to use episodic memory. Cogn. Syst. Res. 12(2): 144-153 (2011) - [j31]Scott D. Lathrop, Samuel Wintermute, John E. Laird:
Exploring the Functional Advantages of Spatial and Visual Cognition From an Architectural Perspective. Top. Cogn. Sci. 3(4): 796-818 (2011) - [c52]Nate Derbinsky, John E. Laird:
A Functional Analysis of Historical Memory Retrieval Bias in the Word Sense Disambiguation Task. AAAI 2011: 663-668 - [c51]Joseph Z. Xu, John E. Laird:
Combining Learned Discrete and Continuous Action Models. AAAI 2011: 1449-1454 - [c50]Nate Derbinsky, John E. Laird:
Effective and Efficient Management of Soar's Working Memory via Base-Level Activation. AAAI Fall Symposium: Advances in Cognitive Systems 2011 - [c49]John Edwin Laird, Nate Derbinsky, Miller Tinkerhess:
A Case Study in Integrating Probabilistic Decision Making and Learning in a Symbolic Cognitive Architecture: Soar Plays Dice. AAAI Fall Symposium: Advances in Cognitive Systems 2011 - [c48]Justin Li, John E. Laird:
Preliminary Evaluation of Long-term Memories for Fulfilling Delayed Intentions. AAAI Fall Symposium: Advances in Cognitive Systems 2011 - [c47]Shiwali Mohan, John E. Laird:
Towards Situated, Interactive, Instructable Agents in a Cognitive Architecture. AAAI Fall Symposium: Advances in Cognitive Systems 2011 - [c46]Shiwali Mohan, John E. Laird:
An Object-Oriented Approach to Reinforcement Learning in an Action Game. AIIDE 2011 - [i2]John E. Laird, Robert E. Wray:
An Architectural Approach to Ensuring Consistency in Hierarchical Execution. CoRR abs/1106.4871 (2011) - 2010
- [c45]Joseph Z. Xu, John E. Laird:
Instance-Based Online Learning of Deterministic Relational Action Models. AAAI 2010: 1574-1579 - [c44]Shiwali Mohan, John E. Laird:
Relational Reinforcement Learning in Infinite Mario. AAAI 2010: 1953-1954 - [c43]Yongjia Wang, John E. Laird:
Efficient Value Function Approximation with Unsupervised Hierarchical Categorization for a Reinforcement Learning Agent. IAT 2010: 197-204
2000 – 2009
- 2009
- [j30]Robert P. Marinier III, John E. Laird, Richard L. Lewis:
A computational unification of cognitive behavior and emotion. Cogn. Syst. Res. 10(1): 48-69 (2009) - [j29]Pat Langley, John E. Laird, Seth Rogers:
Cognitive architectures: Research issues and challenges. Cogn. Syst. Res. 10(2): 141-160 (2009) - [c42]Nate Derbinsky, John E. Laird:
Efficiently Implementing Episodic Memory. ICCBR 2009: 403-417 - 2008
- [c41]Samuel Wintermute, John E. Laird:
Bimodal Spatial Reasoning with Continuous Motion. AAAI 2008: 1331-1337 - [c40]John E. Laird:
Extending the Soar Cognitive Architecture. AGI 2008: 224-235 - 2007
- [c39]Andrew Nuxoll, John E. Laird:
Extending Cognitive Architecture with Episodic Memory. AAAI 2007: 1560-1564 - [c38]Samuel Wintermute, John E. Laird:
Predicate Projection in a Bimodal Spatial Reasoning System. AAAI 2007: 1572-1577 - [c37]Samuel Wintermute, Joseph Z. Xu, John E. Laird:
SORTS: A Human-Level Approach to Real-Time Strategy AI. AIIDE 2007: 55-60 - 2006
- [j28]Tolga Könik, John E. Laird:
Learning goal hierarchies from structured observations and expert annotations. Mach. Learn. 64(1-3): 263-287 (2006) - [e3]John E. Laird, Jonathan Schaeffer:
Proceedings of the Second Artificial Intelligence and Interactive Digital Entertainment Conference, June 20-23, 2006, Marina del Rey, California, USA. The AAAI Press 2006, ISBN 978-1-57735-235-8 [contents] - 2005
- [j27]Robert E. Wray, John E. Laird, Andrew Nuxoll, Devvan Stokes, Alex Kerfoot:
Synthetic Adversaries for Urban Combat Training. AI Mag. 26(3): 82-92 (2005) - [j26]Douglas J. Pearson, John E. Laird:
Incremental Learning of Procedural Planning Knowledge in Challenging Environments. Comput. Intell. 21(4): 414-439 (2005) - [j25]Shelley Nason, John E. Laird:
Soar-RL: integrating reinforcement learning with Soar. Cogn. Syst. Res. 6(1): 51-59 (2005) - [e2]R. Michael Young, John E. Laird:
Proceedings of the First Artificial Intelligence and Interactive Digital Entertainment Conference, June 1-5, 2005, Marina del Rey, California, USA. AAAI Press 2005, ISBN 1-57735-235-1 [contents] - 2004
- [c36]Brian Magerko, John E. Laird, Mazin Assanie, Alex Kerfoot, Devvan Stokes:
AI Characters and Directors for Interactive Computer Games. AAAI 2004: 877-883 - [c35]Robert E. Wray, John E. Laird, Andrew Nuxoll, Devvan Stokes, Alex Kerfoot:
Synthetic Adversaries for Urban Combat Training. AAAI 2004: 923-930 - [c34]John E. Laird:
A Hands-on Tutorial for Building Agent Models in Soar. ICCM 2004 - [c33]Robert P. Marinier III, John E. Laird:
Toward a Comprehensive Computational Model of Emotions and Feelings. ICCM 2004: 172-177 - [c32]Shelley Nason, John E. Laird:
Integrating Reinforcement Learning with Soar. ICCM 2004: 208-213 - [c31]Andrew Nuxoll, John E. Laird:
A Cognitive Model of Episodic Memory Integrated with a General Cognitive Architecture. ICCM 2004: 220-225 - [c30]John E. Laird, Andrew Nuxoll:
Comprehensive Working Memory Activation in Soar. ICCM 2004: 226-230 - [c29]Tolga Könik, John E. Laird:
Learning Goal Hierarchies from Structured Observations and Expert Annotations. ILP 2004: 198-215 - 2003
- [j24]Robert E. Wray III, John E. Laird:
An Architectural Approach to Ensuring Consistency in Hierarchical Execution. J. Artif. Intell. Res. 19: 355-398 (2003) - [c28]Scott A. Wallace, John E. Laird:
Behavior Bounding: Toward Effective Comparisons of Agents & Humans. IJCAI 2003: 727-732 - 2002
- [j23]John E. Laird:
Research in human-level AI using computer games. Commun. ACM 45(1): 32-35 (2002) - [j22]Kenneth D. Forbus, John E. Laird:
Guest Editors' Introduction: AI and the Entertainment Industry. IEEE Intell. Syst. 17(4): 15-16 (2002) - [c27]Bruce S. Elenbogen, John E. Laird, Richard J. Enbody, Chris McDonald, Peter B. Henderson, Richard Nau, Steven L. Tanimoto:
Mathematics preparation for undergraduate degrees in computer science. SIGCSE 2002: 98-99 - 2001
- [j21]John E. Laird, Michael van Lent:
Human-Level AI's Killer Application: Interactive Computer Games. AI Mag. 22(2): 15-26 (2001) - [j20]Lorraine M. Fesq, Ella M. Atkins, Lina Khatib, Charles Pecheur, Paul R. Cohen, Lynn Andrea Stein, Michael van Lent, John E. Laird, Alessandro Provetti, Tran Cao Son:
AAAI 2001 Spring Symposium Series Reports. AI Mag. 22(3): 117-122 (2001) - [j19]John E. Laird:
Using a Computer Game to Develop Advanced AI. Computer 34(7): 70-75 (2001) - [c26]John E. Laird:
It knows what you're going to do: adding anticipation to a Quakebot. Agents 2001: 385-392 - [c25]Michael van Lent, John E. Laird:
Learning procedural knowledge through observation. K-CAP 2001: 179-186 - 2000
- [c24]John E. Laird, Michael van Lent:
Human-Level AI's Killer Application: Interactive Computer Games. AAAI/IAAI 2000: 1171-1178
1990 – 1999
- 1999
- [j18]Randolph M. Jones, John E. Laird, Paul E. Nielsen, Karen J. Coulter, Patrick G. Kenny, Frank V. Koss:
Automated Intelligent Pilots for Combat Flight Simulation. AI Mag. 20(1): 27-41 (1999) - [c23]Michael van Lent, John E. Laird, Josh Buckman, Joe Hartford, Steve Houchard, Kurt Steinkraus, Russ Tedrake:
Intelligent Agents in Computer Games. AAAI/IAAI 1999: 929-930 - [c22]Scott A. Wallace, John E. Laird:
Toward a Methodology for AI Architecture Evaluation: Comparing Soar and CLIPS. ATAL 1999: 117-131 - [c21]Michael van Lent, John E. Laird:
Learning Hierarchical Performance Knowledge by Observation. ICML 1999: 229-238 - 1998
- [j17]John E. Laird, Randolph M. Jones, Paul E. Nielsen:
Knowledge-based Multi-agent Coordination. Presence Teleoperators Virtual Environ. 7(6): 547-563 (1998) - [c20]Robert E. Wray III, John E. Laird:
Maintaining Consistency in Hierarchical Reasoning. AAAI/IAAI 1998: 928-935 - [c19]Randolph M. Jones, John E. Laird, Paul E. Nielsen:
Automated Intelligent Pilots for Combat Flight Simulation. AAAI/IAAI 1998: 1047-1054 - [c18]Robert E. Wray III, John E. Laird:
Ensuring Reasoning Consistency in Hierarchical Architectures. AAAI/IAAI 1998: 1206 - [c17]Randolph M. Jones, John E. Laird, Paul E. Nielsen:
Real-Time Intelligent Characters for a Non-Visual Simulation Environment. CA 1998: 11-18 - 1997
- [j16]John E. Laird, Douglas J. Pearson, Scott B. Huffman:
Knowledge-Directed Adaptation in Multi-Level Agents. J. Intell. Inf. Syst. 9(3): 261-275 (1997) - 1996
- [j15]Craig S. Miller, John E. Laird:
Accounting for Graded Performance within a Discrete Search Framework. Cogn. Sci. 20(4): 499-537 (1996) - [c16]Robert E. Wray III, John E. Laird, Randolph M. Jones:
Compilation of Non-Contemporaneous Constraints. AAAI/IAAI, Vol. 1 1996: 771-778 - 1995
- [j14]Milind Tambe, W. Lewis Johnson, Randolph M. Jones, Frank V. Koss, John E. Laird, Paul S. Rosenbloom, Karl Schwamb:
Intelligent Agents for Interactive Simulation Environments. AI Mag. 16(1): 15-39 (1995) - [j13]Robert E. Wray III, Ronald Chong, Joseph Perry Phillips, Seth Rogers, William Walsh, John E. Laird:
Organizing Information in Mosaic: A Classroom Experiment. Comput. Networks ISDN Syst. 28(1&2): 167-178 (1995) - [j12]Scott B. Huffman, John E. Laird:
Flexibly Instructable Agents. J. Artif. Intell. Res. 3: 271-324 (1995) - [c15]John E. Laird, Randolph M. Jones, Paul E. Nielsen:
Multiagent Coordination in Distributed Interactive Battlefield Simulations. ICMAS 1995: 456 - [c14]Douglas J. Pearson, John E. Laird:
Toward Incremental Knowledge Correction for Agents in Complex Environments. Machine Intelligence 15 1995: 185-204 - [i1]Scott B. Huffman, John E. Laird:
Flexibly Instructable Agents. CoRR abs/cs/9511101 (1995) - 1994
- [c13]Scott B. Huffman, John E. Laird:
Learning from Highly Flexible Tutorial Instruction. AAAI 1994: 506-512 - 1993
- [j11]Paul S. Rosenbloom, John E. Laird:
On Unified Theories of Cognition: A Response to the Reviews. Artif. Intell. 59(1-2): 389-413 (1993) - [j10]Douglas J. Pearson, Scott B. Huffman, Mark B. Willis, John E. Laird, Randolph M. Jones:
A symbolic solution to intelligent real-time control. Robotics Auton. Syst. 11(3-4): 279-291 (1993) - [c12]Scott B. Huffman, John E. Laird:
Instructo-Soar: Learning from Interactive Natural Language Instructions (Video Abstract). AAAI 1993: 857 - [c11]Douglas J. Pearson, Randolph M. Jones, John E. Laird:
AIR-SOAR: Intelligent Multi-Level Control. AAAI 1993: 860-861 - [c10]Scott B. Huffman, John E. Laird:
Learning Procedures from Interactive Natural Language Instructions. ICML 1993: 143-150 - 1992
- [j9]John E. Laird, Paul S. Rosenbloom:
In Pursuit of Mind: The Research of Allen Newell. AI Mag. 13(4): 17-45 (1992) - 1991
- [j8]Paul S. Rosenbloom, John E. Laird, Allen Newell, Robert McCarl:
A Preliminary Analysis of the Soar Architecture as a Basis for General Intelligence. Artif. Intell. 47(1-3): 289-325 (1991) - [j7]