Saurabh Paul, Christos Boutsidis, et al.
JMLR
I consider a logical framework for modeling uncertainty, based on the use of possible worlds, that incorporates knowledge, probability, and time. This turns out to be a powerful approach for modeling many problems of interest. I show how it can be used to give insights into (among other things) several well-known puzzles.
Saurabh Paul, Christos Boutsidis, et al.
JMLR
Joxan Jaffar
Journal of the ACM
Rakesh Mohan, Ramakant Nevatia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cristina Cornelio, Judy Goldsmith, et al.
JAIR