On Condensing a Sequence of Updates in Answer-Set Programming
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 1097-1102.
Abstract
Update semantics for Answer-Set Programming assign models to sequences of answer-set programs which result from the iterative process of updating programs by programs. Each program in the sequence represents an update of the preceding ones. One of the enduring problems in this context is state condensing, or the problem of determining a single logic program that faithfully represents the sequence of programs. Such logic program should 1) be written in the same alphabet, 2) have the same stable models, and 3) be equivalent to the sequence of programs when subject to further updates. It has been known for more than a decade that update semantics easily lead to non-minimal stable models, so an update sequence cannot be represented by a single non-disjunctive program. On the other hand, more expressive classes of programs were never considered, mainly because it was not clear how they could be updated further. In this paper we solve the state condensing problem for two foundational rule update semantics, using nested logic programs. Furthermore, we also show that disjunctive programs with default negation in the head can be used for the same purpose.
@inproceedings{ijcai2013p166,
title = {On Condensing a Sequence of Updates in Answer-Set Programming},
author = {Slota, Martin and Leite, João},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {1097--1102},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/166},
}
TY - CPAPER TI - On Condensing a Sequence of Updates in Answer-Set Programming AU - Slota, Martin AU - Leite, João T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 1097 EP - 1102 UR - https://ijcai.org/proceedings/2013/166 ER -Copied
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