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Domain-Splitting Generalized Nogoods from Restarts
2011
Baptista and Azevedo 2011
The use of restarts techniques associated with learning nogoods in solving Constraint Satisfaction Problems (CSPs) is starting to be considered of major importance for backtrack search algorithms. Recent developments show how to learn nogoods from restarts and that those nogoods are essential when using restarts. Using a backtracking search algorithm, with 2-way branching, generalized nogoods are learned from the last branch of the search tree, immediately before the restart occurs. In this paper we further generalized the learned nogoods but now using domain-splitting branching and set branching. We believe that the use of restarts and learning of domain-splitting generalized nogoods will improve backtrack search algorithms for certain classes of problems.
In proceedings
Luís Baptista, Francisco Azevedo
Luís Antunes, H. S. Pinto
Progress in Artificial Intelligence: Proceedings of the 15th Portuguese Conference on Artificial Intelligence (EPIA 2011)
LNAI
Springer
-
7026
679-689
978-3-642-24768-2
0302-9743
-
-
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Luís Baptista and Francisco Azevedo, Domain-Splitting Generalized Nogoods from Restarts, in: Luís Antunes and H. S. Pinto (eds), Progress in Artificial Intelligence: Proceedings of the 15th Portuguese Conference on Artificial Intelligence (EPIA 2011), LNAI, Springer, Vol. 7026, ISBN 978-3-642-24768-2, ISSN 0302-9743, Pag. 679-689, 2011.
<a href="/people/members/view.php?code=0ec710f4aed9065fb0a84758926e4bc2" class="author">Luís Baptista</a> and <a href="/people/members/view.php?code=f260a0cb31e0c92628691f7473b16e98" class="author">Francisco Azevedo</a>, <b>Domain-Splitting Generalized Nogoods from Restarts</b>, in: Luís Antunes and H. S. Pinto (eds), <u>Progress in Artificial Intelligence: Proceedings of the 15th Portuguese Conference on Artificial Intelligence (EPIA 2011)</u>, LNAI, <a href="http://www.springer.com" title="Link to external entity..." target="_blank" class="publisher">Springer</a>, Vol. 7026, ISBN 978-3-642-24768-2, ISSN 0302-9743, Pag. 679-689, 2011.
@inproceedings {Baptista and Azevedo 2011, author = {Lu\'{\i}s Baptista and Francisco Azevedo}, editor = {Lu\'{\i}s Antunes and H. S. Pinto}, title = {Domain-Splitting Generalized Nogoods from Restarts}, booktitle = {Progress in Artificial Intelligence: Proceedings of the 15th Portuguese Conference on Artificial Intelligence (EPIA 2011)}, series = {LNAI}, publisher = {Springer}, volume = {7026}, pages = {679-689}, isbn = {978-3-642-24768-2}, issn = {0302-9743}, abstract = {The use of restarts techniques associated with learning nogoods in solving Constraint Satisfaction Problems (CSPs) is starting to be considered of major importance for backtrack search algorithms. Recent developments show how to learn nogoods from restarts and that those nogoods are essential when using restarts. Using a backtracking search algorithm, with 2-way branching, generalized nogoods are learned from the last branch of the search tree, immediately before the restart occurs. In this paper we further generalized the learned nogoods but now using domain-splitting branching and set branching. We believe that the use of restarts and learning of domain-splitting generalized nogoods will improve backtrack search algorithms for certain classes of problems.}, year = {2011}, }
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