James R. Wright
James R. Wright
Подтвержден адрес электронной почты в домене ualberta.ca - Главная страница
Beyond equilibrium: Predicting human behavior in normal-form games
JR Wright, K Leyton-Brown
Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010
Deep learning for predicting human strategic behavior
JS Hartford, JR Wright, K Leyton-Brown
Advances in neural information processing systems 29, 2016
Level-0 Meta-Models for Predicting Human Behavior in Games
JR Wright, K Leyton-Brown
Proceedings of the Fifteenth ACM Conference on Economics and Computation …, 2014
Mechanical TA: Partially Automated High-Stakes Peer Grading
JR Wright, C Thornton, K Leyton-Brown
ACM Technical Symposium on Computer Science Education (ACM-SIGCSE), 2015
Incentivizing evaluation with peer prediction and limited access to ground truth
XA Gao, JR Wright, K Leyton-Brown
Artificial Intelligence 275, 618-638, 2019
Predicting Human Behavior in Unrepeated, Simultaneous-Move Games
JR Wright, K Leyton-Brown
Games and Economic Behavior 106, 16-37, 2017
Behavioral game theoretic models: a Bayesian framework for parameter analysis.
JR Wright, K Leyton-Brown
AAMAS, 921-930, 2012
How can machine learning aid behavioral marketing research?
L Hagen, K Uetake, N Yang, B Bollinger, AJB Chaney, D Dzyabura, ...
Marketing Letters 31 (4), 361-370, 2020
Why do software developers use static analysis tools? a user-centered study of developer needs and motivations
LNQ Do, J Wright, K Ali
IEEE Transactions on Software Engineering, 2020
Learning when to stop searching
DG Goldstein, RP McAfee, S Suri, JR Wright
Management Science 66 (3), 1375-1394, 2020
Hindsight and sequential rationality of correlated play
D Morrill, R D'Orazio, R Sarfati, M Lanctot, JR Wright, AR Greenwald, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 5584-5594, 2021
Level-0 Models for Predicting Human Behavior in Games
JR Wright, K Leyton-Brown
Journal of Artificial Intelligence Research 64, 357-383, 2019
Efficient deviation types and learning for hindsight rationality in extensive-form games
D Morrill, R D’Orazio, M Lanctot, JR Wright, M Bowling, AR Greenwald
International Conference on Machine Learning, 7818-7828, 2021
The spotlight: A general method for discovering systematic errors in deep learning models
G d'Eon, J d'Eon, JR Wright, K Leyton-Brown
2022 ACM Conference on Fairness, Accountability, and Transparency, 1962-1981, 2022
A formal separation between strategic and nonstrategic behavior
JR Wright, K Leyton-Brown
Proceedings of the 21st ACM Conference on Economics and Computation, 535-536, 2020
Alternative Function Approximation Parameterizations for Solving Games: An Analysis of -Regression Counterfactual Regret Minimization
R D'Orazio, D Morrill, JR Wright, M Bowling
arXiv preprint arXiv:1912.02967, 2019
The Role of Accuracy in Algorithmic Process Fairness Across Multiple Domains
M Albach, JR Wright
Proceedings of the 22nd ACM Conference on Economics and Computation, 29-49, 2021
Models of Level-0 Behavior for Predicting Human Behavior in Games
JR Wright, K Leyton-Brown
arXiv preprint arXiv:1609.08923, 2016
Modeling human behavior in strategic settings
JR Wright
University of British Columbia, 2016
Evaluating, Understanding, and Improving Behavioral Game Theory Models For Predicting Human Behavior in Unrepeated Normal-Form Games
JR Wright, K Leyton-Brown
arXiv preprint arXiv:1306.0918, 2013
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