Computing only minimal answers in disjunctive deductive databases

A method is presented for computing minimal answers in disjunctive deductive databases under the disjunctive stable model semantics. Such answers are constructed by repeatedly extending partial answers. Our method is complete (in that every minimal answer can be computed) and does not admit redundancy (in the sense that every partial answer generated can be extended to a minimal answer), whence no non-minimal answer is generated. For stratified databases, the method does not (necessarily) require the computation of models of the database in their entirety. Compilation is proposed as a tool by which problems relating to computational efficiency and the non-existence of disjunctive stable models can be overcome. The extension of our method to other semantics is also considered.Comment: 48 page

Conditional Answer Computation in SOL as Speculative Computation in Multi-Agent Environments1 1This research was supported partly by Grant-in-Aid from The Ministry of Education, Science and Culture of Japan.

AbstractIn this paper, we study speculative computation in a master-slave multi-agent system where reply messages sent from slave agents to a master are always tentative and may change from time to time. In this system, default values used in speculative computation are only partially determined in advance. Inoue et al. [8] formalized speculative computation in such an environment with tentative replies, using the framework of a first-order consequence-finding procedure SOL with the well-known answer literal method. We shall further refine the SOL calculus, using conditional answer computation and skip-preference in SOL. The conditional answer format has an great advantage of explicitly representing how a conclusion depends on tentative replies and defaults, both of which are used to derive the conclusion. The dependency representation is significantly important to avoid unnecessary recomputation of tentative conclusions. The skip-preference has the great ability of preventing irrational/redundant derivations