TY - GEN
T1 - Towards practical tabled abduction in logic programs
AU - Saptawijaya, Ari
AU - Pereira, Luís Moniz
PY - 2013
Y1 - 2013
N2 - Despite its potential as a reasoning paradigm in AI applications, abduction has been on the back burner in logic programming, as abduction can be too difficult to implement, and costly to perform, in particular if abductive solutions are not tabled. If they become tabled, then abductive solutions can be reused, even from one abductive context to another. On the other hand, current Prolog systems, with their tabling mechanisms, are mature enough to facilitate the introduction of tabling abductive solutions (tabled abduction) into them. The concept of tabled abduction has been realized recently in an abductive logic programming system tabdual. Besides tabling abductive solutions, tabdual also relies on the dual transformation. In this paper, we emphasize two tabdual improvements: (1) the dual transformation by need, and (2) a new construct for accessing ongoing abductive solutions, that permits modular mixes between abductive and non-abductive program parts. We apply subsequently these improvements on two distinct problems, and evaluate the performance and the scalability of tabdual on several benchmarks on the basis of these problems, by examining four tabdual variants.
AB - Despite its potential as a reasoning paradigm in AI applications, abduction has been on the back burner in logic programming, as abduction can be too difficult to implement, and costly to perform, in particular if abductive solutions are not tabled. If they become tabled, then abductive solutions can be reused, even from one abductive context to another. On the other hand, current Prolog systems, with their tabling mechanisms, are mature enough to facilitate the introduction of tabling abductive solutions (tabled abduction) into them. The concept of tabled abduction has been realized recently in an abductive logic programming system tabdual. Besides tabling abductive solutions, tabdual also relies on the dual transformation. In this paper, we emphasize two tabdual improvements: (1) the dual transformation by need, and (2) a new construct for accessing ongoing abductive solutions, that permits modular mixes between abductive and non-abductive program parts. We apply subsequently these improvements on two distinct problems, and evaluate the performance and the scalability of tabdual on several benchmarks on the basis of these problems, by examining four tabdual variants.
KW - abductive logic programming
KW - dual transformation
KW - tabled abduction
KW - tabled logic programming
UR - http://www.scopus.com/inward/record.url?scp=84884729032&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40669-0_20
DO - 10.1007/978-3-642-40669-0_20
M3 - Conference contribution
AN - SCOPUS:84884729032
SN - 9783642406683
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 223
EP - 234
BT - Progress in Artificial Intelligence - 16th Portuguese Conference on Artificial Intelligence, EPIA 2013, Proceedings
T2 - 16th Portuguese Conference on Artificial Intelligence, EPIA 2013
Y2 - 9 September 2013 through 12 September 2013
ER -