'Knowing Whether' in Proper Epistemic Knowledge Bases

Proper epistemic knowledge bases (PEKBs) are syntactic knowledge bases that use multi-agent epistemic logic to represent nested multi-agent knowledge and belief. PEKBs have certain syntactic restrictions that lead to desirable computational properties; primarily, a PEKB is a conjunction of modal literals, and therefore contains no disjunction. Sound entailment can be checked in polynomial time, and is complete for a large set of arbitrary formulae in logics Kn and KDn. In this paper, we extend PEKBs to deal with a restricted form of disjunction: 'knowing whether.' An agent i knows whether Q iff agent i knows Q or knows not Q; that is, []Q or []not(Q). In our experience, the ability to represent that an agent knows whether something holds is useful in many multi-agent domains. We represent knowing whether with a modal operator, and present sound polynomial-time entailment algorithms on PEKBs with the knowing whether operator in Kn and KDn, but which are complete for a smaller class of queries than standard PEKBs

Approches légères pour le raisonnement sur les connaissances et les croyances

Dans cette thèse nous étudions un cadre simple dans lequel modéliser les croyances et les connaissances ainsi que leur évolution dans des systèmes multi-agents. La logique standard de représentation des connaissances est très expressive, mais au prix d'une haute complexité calculatoire. Nous proposons ici un cadre qui permet de capturer plus de situations que d'autres approches existantes tout en restant efficace. En particulier, nous considérons l'application de notre logique à la planification épistémique : étant données une situation initiale et des actions possibles, peut-on atteindre un but fixé ? Cela peut signifier savoir à qui poser des questions pour apprendre des informations, faire en sorte de ne pas être remarquée lorsque l'on lit le courrier de quelqu'un d'autre, ou empêcher quelqu'un d'entendre nos secrets. Nous considérons aussi de possibles extensions à des logiques de croyance, ainsi que les liens entre notre système et d'autres cadres proches.In this thesis we study a lightweight framework in which to model knowledge and beliefs and the evolution thereof in multiagent systems. The standard logic used for this is very expressive, but this comes at a high cost in terms of computational efficiency. We here propose a framework which captures more than other existing approaches while remaining cost-effective. In particular, we show its applicability to epistemic planning: given an initial situation and some possible actions, can we find a way to reach our desired goal? This might mean knowing who to ask in order to learn something, making sure we aren't seen when reading someone else's mail, or preventing someone from overhearing our secrets. We also discuss possible extensions to logics of belief, and the relations between our framework and other related approaches