Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations
© 2019 International Joint Conferences on Artificial Intelligence. All rights reserved. Temporal logics are useful for providing concise descriptions of system behavior, and have been successfully used as a language for goal definitions in task planning. Prior works on inferring temporal logic speci...
Main Authors: | Kim, Joseph (Author), Muise, Christian (Author), Shah, Ankit Jayesh (Author), Agarwal, Shubham (Author), Shah, Julie A (Author) |
---|---|
Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), MIT-IBM Watson AI Lab (Contributor) |
Format: | Article |
Language: | English |
Published: |
International Joint Conferences on Artificial Intelligence,
2021-11-04T13:51:00Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
Bayesian inference of temporal task specifications from demonstrations
by: Shah, Ankit Jayesh, et al.
Published: (2020) -
Bayesianism and inference to the best explanation
by: Valeriano IRANZO
Published: (2008-01-01) -
Can Bayesianism and Inference to the Best Explanation be Friends?
by: Stewart, Rush Tyler
Published: (2010) -
Can Bayesianism and Inference to the Best Explanation be Friends?
by: Stewart, Rush Tyler
Published: (2010) -
Interactive Robot Training for Temporal Tasks
by: Shah, Ankit Jayesh, et al.
Published: (2021)