TY - GEN
T1 - Querying sequential and concurrent horn transaction logic programs using tabling techniques
AU - Fodor, Paul
PY - 2008
Y1 - 2008
N2 - In this poster we describe the tabling techniques for Sequential and Concurrent Horn Transaction Logic. Horn Transaction Logic is an extension of classical logic programming with state updates and it has a SLD-style evaluation algorithm. This SLD-style algorithm enters into infinite loops when computing answers to many recursive programs when they change the underlying state of the knowledge base. We solve this problem by tabling (caching) the calls, call states and answers (unifications and return states) in a searchable structure for the Sequential Transaction Logic, or building a graph for the query and memoize the "hot" vertices (vertices, currently, possible to execute) for the Propositional Concurrent Transaction Logic, so that the same call is not re-executed ad infinum. With these techniques, we can efficiently compute queries to transaction logic programs, and when the underlying programs have the bounded term-depth property (Transaction Datalog) the techniques are guaranteed to terminate. The applications of these techniques promise termination and great improvements in the uses of transaction logic: state-changing systems, artificial intelligence planning, dynamic constraints on transaction execution, workflow modeling and verification, and systems involving financial transactions.
AB - In this poster we describe the tabling techniques for Sequential and Concurrent Horn Transaction Logic. Horn Transaction Logic is an extension of classical logic programming with state updates and it has a SLD-style evaluation algorithm. This SLD-style algorithm enters into infinite loops when computing answers to many recursive programs when they change the underlying state of the knowledge base. We solve this problem by tabling (caching) the calls, call states and answers (unifications and return states) in a searchable structure for the Sequential Transaction Logic, or building a graph for the query and memoize the "hot" vertices (vertices, currently, possible to execute) for the Propositional Concurrent Transaction Logic, so that the same call is not re-executed ad infinum. With these techniques, we can efficiently compute queries to transaction logic programs, and when the underlying programs have the bounded term-depth property (Transaction Datalog) the techniques are guaranteed to terminate. The applications of these techniques promise termination and great improvements in the uses of transaction logic: state-changing systems, artificial intelligence planning, dynamic constraints on transaction execution, workflow modeling and verification, and systems involving financial transactions.
UR - https://www.scopus.com/pages/publications/57749086819
M3 - Conference contribution
AN - SCOPUS:57749086819
SN - 9781577353683
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1800
EP - 1801
BT - AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
T2 - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
Y2 - 13 July 2008 through 17 July 2008
ER -