@inproceedings{efe5307851034580968f323957e73536,
title = "Learning effect axioms via probabilistic logic programming",
abstract = "Events have effects on properties of the world; they initiate or terminate these properties at a given point in time. Reasoning about events and their e ects comes naturally to us and appears to be simple, but it is actually quite di cult for a machine to work out the relationships between events and their e ects. Traditionally, effect axioms are assumed to be given for a particular domain and are then used for event recognition. We show how we can automatically learn the structure of effect axioms from example interpretations in the form of short dialogue sequences and use the resulting axioms in a probabilistic version of the Event Calculus for query answering. Our approach is novel, since it can deal with uncertainty in the recognition of events as well as with uncertainty in the relationship between events and their effects. The suggested probabilistic Event Calculus dialect directly subsumes the logic-based dialect and can be used for exact as well as a for inexact inference.",
keywords = "Effect axioms, Event calculus, Event recognition, Probabilistic logic programming, Reasoning under uncertainty",
author = "Rolf Schwitter",
note = "Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.; International Conference on Logic Programming (33rd : 2017) ; Conference date: 28-08-2017 Through 01-09-2017",
year = "2018",
month = feb,
day = "1",
doi = "10.4230/OASIcs.ICLP.2017.8",
language = "English",
series = "OASIcs",
publisher = "Dagstuhl Publishing",
pages = "1--15",
editor = "Ricardo Rocha and Son, {Tran Cao} and Christopher Mears and Neda Saeedloei",
booktitle = "ICLP 2017",
address = "Germany",
}