Probablistic Temporal Networks with Ordinary Distributions: Theory, Robustness and Expected Utility. Saint-Guillain, M., Vaquero, T. S., Chien, S., Agrawal, J., & Abrahams, J. Journal of Artificial Intelligence Research, 17:1091–1136, AI Access Foundation, Inc, 2021.
Probablistic Temporal Networks with Ordinary Distributions: Theory, Robustness and Expected Utility [link]Paper  bibtex   16 downloads  
@article{saint_guillain_et_al_JAIR21,
	title        = {Probablistic Temporal Networks with Ordinary Distributions: Theory, Robustness and Expected Utility},
	author       = {Saint-Guillain, M. and Vaquero, T. S. and Chien, S. and Agrawal, J. and Abrahams, J.},
	year         = 2021,
	journal      = {Journal of Artificial Intelligence Research},
	publisher    = {AI Access Foundation, Inc},
	volume       = 17,
	pages        = {1091--1136},
	url          = {https://doi.org/10.1613/jair.1.13019},
	clearance    = {CL\#21-3895},
	project      = {m2020}
}

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