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ORCIDThomas R. Shultz
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- affiliation: McGill University, Department of Psychology, Montreal, QC, Canada
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2020 – today
- 2024
[i8]Thomas R. Shultz, Jamie Wise, Ardavan Salehi Nobandegani:
GPT-4 Understands Discourse at Least as Well as Humans Do. CoRR abs/2403.17196 (2024)- 2023
- [c51]Zhe Fan, Zilong Wang, Thomas R. Shultz:
A Perceptual Front-End for Probability Learning: Object Detection with YOLO. CogSci 2023 - [c50]Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz:
AI Agents Learn to Trust. CogSci 2023 - [c49]Ardavan Salehi Nobandegani, Thomas R. Shultz:
Neural Network Modeling of Pure Reasoning in Preverbal Infants. CogSci 2023 - [c48]Thomas R. Shultz, Ardavan Salehi Nobandegani, Zilong Wang:
A Neural Model of Number Comparison with Robust Generalization. CogSci 2023 - [c47]Zilong Wang, Thomas R. Shultz, Ardavan Salehi Nobandegani:
A Computational Model of Children's Learning and Use of Probabilities Across Different Ages. CogSci 2023 - [i7]Ardavan Salehi Nobandegani, Irina Rish, Thomas R. Shultz:
Towards Machines that Trust: AI Agents Learn to Trust in the Trust Game. CoRR abs/2312.12868 (2023) - 2022
- [c46]Yiwei Cao, Ardavan Salehi Nobandegani, Thomas R. Shultz:
A Resource-Rational Process Model of Violation of Cumulative Independence. CogSci 2022 - [c45]Marcel R. Montrey, Thomas R. Shultz:
Ingroup-Biased Copying Promotes Cultural Diversity and Complexity. CogSci 2022 - [c44]Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish:
Cognitive Models as Simulators: The Case of Moral Decision-Making. CogSci 2022 - [c43]Thomas R. Shultz, Ardavan Salehi Nobandegani:
Modeling the Learning and Use of Probability Distributions in Chimpanzees and Humans. CogSci 2022 - [c42]Feng Xia, Ardavan Salehi Nobandegani, Thomas R. Shultz, Rahul Bhui:
A Resource-Rational Process-Level Account of Violation of Stochastic Dominance. CogSci 2022 - [i6]Ardavan Salehi Nobandegani, Thomas R. Shultz, Irina Rish:
Cognitive Models as Simulators: The Case of Moral Decision-Making. CoRR abs/2210.04121 (2022) - 2021
- [c41]Myriam Lizotte, Ardavan Salehi Nobandegani, Thomas R. Shultz:
Emotions in Games: Toward a Unified Process-Level Account. CogSci 2021 - [c40]Ardavan Salehi Nobandegani, Thomas R. Shultz, Laurette Dubé:
A Unified, Resource-Rational Account of the Allais and Ellsberg Paradoxes. CogSci 2021 - 2020
- [j14]Ardavan Salehi Nobandegani, Thomas R. Shultz:
A Resource-Rational, Process-Level Account of the St. Petersburg Paradox. Top. Cogn. Sci. 12(1): 417-432 (2020) - [c39]Ardavan Salehi Nobandegani, Thomas R. Shultz:
The St. Petersburg Paradox: A Fresh Algorithmic Perspective. AAAI 2020: 13689-13692 - [c38]Ardavan Salehi Nobandegani, Constance Destais, Thomas R. Shultz:
A Resource-Rational Process Model of Fairness in the Ultimatum Game. CogSci 2020 - [c37]Ardavan Salehi Nobandegani, Thomas R. Shultz:
A Resource-Rational Mechanistic Account of Human Coordination Strategies. CogSci 2020 - [c36]Thomas R. Shultz, Ardavan Salehi Nobandegani:
Probability Without Counting and Dividing: A Fresh Computational Perspective. CogSci 2020
2010 – 2019
- 2019
- [c35]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 - [c34]Ardavan Salehi Nobandegani, Kevin da Silva Castanheira, Thomas R. Shultz, A. Ross Otto:
A Resource-Rational Mechanistic Approach to One-shot Non-cooperative Games: The Case of Prisoner's Dilemma. CogSci 2019: 863-869 - [c33]Ardavan Salehi Nobandegani, Kevin da Silva Castanheira, Thomas R. Shultz, A. Ross Otto:
A Resource-Rational Process-Level Account of the St. Petersburg Paradox. CogSci 2019: 870-876 - [c32]Ardavan Salehi Nobandegani, Thomas R. Shultz:
Toward a Formal Science of Heuristics. CogSci 2019: 877-882 - [c31]Marcel R. Montrey, Thomas R. Shultz:
Outgroup Homogeneity Bias Causes Ingroup Favoritism. CogSci 2019: 2392-2398 - [c30]Peter Helfer, Thomas R. Shultz:
The role of AMPA receptor exchange in systems memory reconsolidation: A computational model. CogSci 2019: 3279 - [c29]Ardavan Salehi Nobandegani, William Campoli, Thomas R. Shultz:
Bringing Order to the Cognitive Fallacy Zoo. CogSci 2019: 3326 - [c28]Ardavan Salehi Nobandegani, Kevin da Silva Castanheira, Timothy O'Donnell, Thomas R. Shultz:
On Robustness: An Undervalued Dimension of Human Rationality. CogSci 2019: 3327 - [c27]Ardavan Salehi Nobandegani, Kevin da Silva Castanheira, Thomas R. Shultz, A. Ross Otto:
Decoy Effect and Violation of Betweenness in Risky Decision Making: A Resource-Rational Mechanistic Account. CogSci 2019: 3328 - [c26]Ashley Stendel, Thomas R. Shultz:
An Attractor Neural-network Simulation of Decision Making. CogSci 2019: 3364 - [c25]Lie Yu, Ardavan Salehi Nobandegani, Thomas R. Shultz:
Neural Network Modeling of Learning to Actively Learn. CogSci 2019: 3392 - [c24]Kevin da Silva Castanheira, Ardavan Salehi Nobandegani, Thomas R. Shultz, A. Ross Otto:
Contextual Effects in Value-Based Decision Making: A Resource-Rational Mechanistic Account. CogSci 2019: 3440 - 2018
- [j13]Peter Helfer
, Thomas R. Shultz:
Coupled feedback loops maintain synaptic long-term potentiation: A computational model of PKMzeta synthesis and AMPA receptor trafficking. PLoS Comput. Biol. 14(5) (2018) - [c23]Ardavan Salehi Nobandegani, Kevin da Silva Castanheira, A. Ross Otto, Thomas R. Shultz:
Over-representation of Extreme Events in Decision-Making: A Rational Metacognitive Account. CogSci 2018 - [c22]Ardavan Salehi Nobandegani, Thomas R. Shultz:
Example Generation Under Constraints Using Cascade Correlation Neural Nets. CogSci 2018 - [i5]Ardavan Salehi Nobandegani, Kevin da Silva Castanheira, A. Ross Otto, Thomas R. Shultz:
Over-representation of Extreme Events in Decision-Making: A Rational Metacognitive Account. CoRR abs/1801.09848 (2018) - [i4]Ardavan Salehi Nobandegani, William Campoli, Thomas R. Shultz:
Bringing Order to the Cognitive Fallacy Zoo. CoRR abs/1810.06710 (2018) - 2017
- [c21]Ardavan Salehi Nobandegani, Thomas R. Shultz:
Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models. CogSci 2017 - [r2]Thomas R. Shultz, Scott E. Fahlman:
Cascade Correlation. Encyclopedia of Machine Learning and Data Mining 2017: 171-180 - [i3]Ardavan Salehi Nobandegani, Thomas R. Shultz:
Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models. CoRR abs/1701.05004 (2017) - 2016
- [j12]Milad Kharratzadeh, Thomas R. Shultz:
Neural implementation of probabilistic models of cognition. Cogn. Syst. Res. 40: 99-113 (2016) - 2015
- [c20]Milad Kharratzadeh, Marcel R. Montrey, Alex Metz, Thomas R. Shultz:
Resolving Rogers' Paradox with Specialized Hybrid Learners. CogSci 2015 - [c19]Milad Kharratzadeh, Thomas R. Shultz:
Probability Matching via Deterministic Neural Networks. CoCo@NIPS 2015 - [i2]Milad Kharratzadeh, Thomas R. Shultz:
Neural Implementation of Probabilistic Models of Cognition. CoRR abs/1501.03209 (2015) - 2014
- [j11]Frédéric Dandurand, Thomas R. Shultz:
A comprehensive model of development on the balance-scale task. Cogn. Syst. Res. 31-32: 1-25 (2014) - [c18]Artem Kaznatcheev, Marcel R. Montrey, Thomas R. Shultz:
Evolving useful delusions: Subjectively rational selfishness leads to objectively irrational cooperation. CogSci 2014 - 2013
- [j10]Max Hartshorn, Artem Kaznatcheev, Thomas R. Shultz:
The Evolutionary Dominance of Ethnocentric Cooperation. J. Artif. Soc. Soc. Simul. 16(3) (2013) - [c17]Peter Helfer, Thomas R. Shultz, Oliver Hardt, Karim Nader:
A Computational Model of Systems Memory Reconsolidation. CogSci 2013 - [c16]Milad Kharratzadeh, Thomas R. Shultz:
Neural-network Modelling of Bayesian Learning and Inference. CogSci 2013 - [i1]Thomas R. Shultz:
Managing Uncertainty in Rule Based Cognitive Models. CoRR abs/1304.1083 (2013) - 2012
- [j9]Frédéric Dandurand, Thomas R. Shultz, Arnaud Rey:
Including cognitive biases and distance-based rewards in a connectionist model of complex problem solving. Neural Networks 25: 41-56 (2012) - [c15]Frédéric Dandurand, Denis Cousineau, Thomas R. Shultz:
Solving nonogram puzzles by reinforcement learning. CogSci 2012 - [c14]Thomas R. Shultz, Eric Doty, Frédéric Dandurand:
Knowing When to Abandon Unproductive Learning. CogSci 2012 - 2011
- [j8]Thomas R. Shultz, Benjamin Kuipers:
Understanding Psychological Development in Biological and Artificial Agents: Report on the International Conference on Development and Learning (ICDL 2010). IEEE Trans. Auton. Ment. Dev. 3(1): 4-5 (2011) - [c13]Frédéric Dandurand, Thomas R. Shultz:
A Fresh Look at Vocabulary Spurts. CogSci 2011 - [c12]Artem Kaznatcheev, Thomas R. Shultz:
Ethnocentrism Maintains Cooperation, but Keeping One's Children Close Fuels It. CogSci 2011 - [c11]Heather Prime, Thomas R. Shultz:
Explicit Bayesian Reasoning with Frequencies, Probabilities, and Surprisals. CogSci 2011 - 2010
- [c10]Thomas R. Shultz, Vincent G. Berthiaume, Frédéric Dandurand:
Bootstrapping syntax from morpho-phonology. ICDL 2010: 52-57 - [c9]Marcel R. Montrey, Thomas R. Shultz:
Evolution of social learning strategies. ICDL 2010: 95-100 - [c8]Vanessa C. Evans, Vincent G. Berthiaume, Thomas R. Shultz:
Toddlers' transitions on non-verbal false-belief tasks involving a novel location: A constructivist connectionist model. ICDL 2010: 225-230 - [e1]Benjamin Kuipers, Thomas R. Shultz, Alexander Stoytchev, Chen Yu:
2010 IEEE 9th International Conference on Development and Learning, ICDL 2010, Ann Arbor, MI, USA, August 18-21, 2010. IEEE 2010, ISBN 978-1-4244-6902-4 [contents] - [r1]Thomas R. Shultz, Scott E. Fahlman:
Cascade-Correlation. Encyclopedia of Machine Learning 2010: 139-147
2000 – 2009
- 2009
- [j7]Frédéric Dandurand, Thomas R. Shultz:
Connectionist Models of Reinforcement, Imitation, and Instruction in Learning to Solve Complex Problems. IEEE Trans. Auton. Ment. Dev. 1(2): 110-121 (2009) - 2007
- [j6]Frédéric Dandurand, Vincent G. Berthiaume, Thomas R. Shultz:
A systematic comparison of flat and standard cascade-correlation using a student-teacher network approximation task. Connect. Sci. 19(3): 223-244 (2007) - [j5]Thomas R. Shultz, François Rivest, László Egri, Jean-Philippe Thivierge, Frédéric Dandurand:
Could Knowledge-Based Neural Learning be Useful in Developmental Robotics? The Case of Kbcc. Int. J. Humanoid Robotics 4(2): 245-279 (2007) - 2006
- [j4]Thomas R. Shultz, Alan C. Bale:
Neural networks discover a near-identity relation to distinguish simple syntactic forms. Minds Mach. 16(2): 107-139 (2006) - 2004
- [c7]François Rivest, Thomas R. Shultz:
Compositionality in a Knowledge-Based Constructive Learner. AAAI Technical Report (3) 2004: 54-58 - 2001
- [j3]Thomas R. Shultz, François Rivest:
Knowledge-based cascade-correlation: using knowledge to speed learning. Connect. Sci. 13(1): 43-72 (2001) - 2000
- [c6]Thomas R. Shultz, François Rivest:
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning. ICML 2000: 871-878 - [c5]Thomas R. Shultz, François Rivest:
Knowledge-Based Cascade-Correlation. IJCNN (5) 2000: 641-646
1990 – 1999
- 1999
- [j2]Denis Mareschal, Thomas R. Shultz:
Development of Children's Seriation: A Connectionist Approach. Connect. Sci. 11(2): 149-186 (1999) - 1994
- [j1]Thomas R. Shultz, Denis Mareschal, William C. Schmidt:
Modeling Cognitive Development on Balance Scale Phenomena. Mach. Learn. 16(1-2): 57-86 (1994) - [c4]Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Takane:
Analysis of Unstandardized Contributions in Cross Connected Networks. NIPS 1994: 601-608 - 1993
- [c3]Thomas R. Shultz, Jeffrey L. Elman:
Analyzing Cross-Connected Networks. NIPS 1993: 1117-1124 - 1991
- [c2]Thomas R. Shultz:
Simulating Stages of Human Cognitive Development With Connectionist Models. ML 1991: 105-109 - 1990
- [c1]Thomas R. Shultz:
Propagating uncertainty in rule based cognitive modelling. UAI 1990: 33-40
Coauthor Index
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