On the Relation Between Truth Maintenance and Autoepistemic Logic
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 1206-1211.
Abstract
In a recent paper, Konolige has introduced a new version of autoepistemic logic (AE L), which is based on a strong notion of groundedness. We show that it is well-suited for formalizing the concept of justified belief in a non-monotonic truth maintenance system (TMS) . If we consider the justifications of a TMS as formulae of the form La/\...., Lb::Jc, it computes the set of non - modal atoms of a strongly grounded AEL-extension. It is shown that a variant of Dressler's encoding of nonmonotonic justifications in an assumptionbased TMS is correct, and thus also inherits the AEL semantics. We argue that more work is needed to come to a better understanding of backtracking routines and so-called nogood inferences, which are identified as sources of ungrounded conclusions . These results contribute to bridging the gap between theory and implementation in the field of nonmonotonic reasoning .
@inproceedings{ijcai1989p193,
title = {On the Relation Between Truth Maintenance and Autoepistemic Logic},
author = {Reinfrank, Michael and Dressler, Oskar and Brewka, Gerhard},
booktitle = {Proceedings of the Eleventh International Joint Conference on
Artificial Intelligence, {IJCAI-89}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {N. S. Sridharan},
pages = {1206--1211},
year = {1989},
month = {8},
note = {Knowledge Representation},
url = {https://ijcai.org/proceedings/1989/193},
}
TY - CPAPER TI - On the Relation Between Truth Maintenance and Autoepistemic Logic AU - Reinfrank, Michael AU - Dressler, Oskar AU - Brewka, Gerhard T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 1206 EP - 1211 UR - https://ijcai.org/proceedings/1989/193 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: