Combining left and right unlinking for matching a large number of learned rules
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Fast planning through planning graph analysis
Artificial Intelligence
On the analysis of indexing schemes
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Extending Planning Graphs to an ADL Subset
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Using Predicate Abstraction to Generate Heuristic Functions in UPPAAL
Model Checking and Artificial Intelligence
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
Relaxation Refinement: A New Method to Generate Heuristic Functions
Model Checking and Artificial Intelligence
Planned and traversable play-out: a flexible method for executing scenario-based programs
TACAS'07 Proceedings of the 13th international conference on Tools and algorithms for the construction and analysis of systems
Spartacus: A Tableau Prover for Hybrid Logic
Electronic Notes in Theoretical Computer Science (ENTCS)
KLEE: unassisted and automatic generation of high-coverage tests for complex systems programs
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Interactive recommendations in social endorsement networks
Proceedings of the fourth ACM conference on Recommender systems
Extended caching, backjumping and merging for expressive description logics
IJCAR'12 Proceedings of the 6th international joint conference on Automated Reasoning
| Hi-index | 0.00 |
Let us consider the following problem: Given a (probably huge) set of sets S and a query set g, is there some set s Ε S such s ⊆ q; that This problem occurs in at least four application areas: the matching of a large number (usually several 100,000s) of production rules, the processing of queries in data bases supporting set-valued attributes, the identification of inconsistent subgoals during artificial intelligence planning and the detection of potential periodic chains in labeled tableau systems for modal logics. In this paper, we introduce a data structure and algorithm that allow a compact representation of such a huge set of sets and an efficient answering of subset and superset queries. The algorithm has been used successfully in the IPP system and enabled this planner to win the ADL track of the first planning competition.