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

MIM-Logic: a logic for reasoning about molecular interaction maps

Les séries de réactions biochimiques apparaissant au cœur d'une cellule forme ce qu'on appelle des voies métaboliques. La plupart de ces voies sont très complexes impliquant un grand nombre de protéines et d'enzymes. Une représentation logique de ces réseaux contribue au raisonnement à propos de ces voies en général, allant du fait de répondre à certaines questions, compléter des arcs et nœuds manquant, et trouver des incohérences. Dans ce contexte on propose un nouveau model logique basé sur un fragment de logique de premier ordre capable de décrire les réactions apparaissant dans des Molecular Interaction Maps. On propose aussi une méthode de déduction automatique efficace capable de répondre aux questions par déduction pour prédire les résultats des réactions et par abduction pour trouver les états des protéines et de leurs réactions. Cette méthode automatique est basée sur une procédure de traduction qui élimine les quantificateurs des formules de logique premier ordre.The series of biochemical reactions that occur within a cell form what we call Metabolic Pathways. Most of them can be quite intricate and involve many proteins and enzymes. Logical representations of such networks can help reason about them in general, where the reasoning can range from answering some queries, to completing missing nodes and arcs, and finding inconsistencies. This work proposes a new logical model based on a fragment of first-order logic capable of describing reactions that appear in a Molecular Interaction Maps. We also propose an efficient automated deduction method that can answer queries by deduction to predict reaction results or by abductive reasoning to find reactions and protein states. This automated deduction method is based on a translation procedure that transforms first-order formulas into quantifier free formulas