TY - GEN
T1 - Magically constraining the inverse method using dynamic polarity assignment
AU - Chaudhuri, Kaustuv
PY - 2010/1/1
Y1 - 2010/1/1
N2 - Given a logic program that is terminating and mode-correct in an idealised Prolog interpreter (i.e., in a top-down logic programming engine), a bottom-up logic programming engine can be used to compute exactly the same set of answers as the top-down engine for a given mode-correct query by rewriting the program and the query using the Magic Sets Transformation (MST). In previous work, we have shown that focusing can logically characterise the standard notion of bottom-up logic programming if atomic formulas are statically given a certain polarity assignment. In an analogous manner, dynamically assigning polarities can characterise the effect of MST without needing to transform the program or the query. This gives us a new proof of the completeness of MST in purely logical terms, by using the general completeness theorem for focusing. As the dynamic assignment is done in a general logic, the essence of MST can potentially be generalised to larger fragments of logic.
AB - Given a logic program that is terminating and mode-correct in an idealised Prolog interpreter (i.e., in a top-down logic programming engine), a bottom-up logic programming engine can be used to compute exactly the same set of answers as the top-down engine for a given mode-correct query by rewriting the program and the query using the Magic Sets Transformation (MST). In previous work, we have shown that focusing can logically characterise the standard notion of bottom-up logic programming if atomic formulas are statically given a certain polarity assignment. In an analogous manner, dynamically assigning polarities can characterise the effect of MST without needing to transform the program or the query. This gives us a new proof of the completeness of MST in purely logical terms, by using the general completeness theorem for focusing. As the dynamic assignment is done in a general logic, the essence of MST can potentially be generalised to larger fragments of logic.
U2 - 10.1007/978-3-642-16242-8_15
DO - 10.1007/978-3-642-16242-8_15
M3 - Conference contribution
AN - SCOPUS:85037529832
SN - 364216241X
SN - 9783642162411
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 202
EP - 216
BT - Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings
PB - Springer Verlag
ER -