This paper presents an extension of propositional dynamic database logic in which the speciication writer can specify arbitrary database transactions declaratively. Since declaratively speciied transactions are under-speciied, the speciication must be supplemented with a frame assumption about what does not change as the result of a transaction. In addition , static database constraints imply p...

Probabilistic relational models (PRMs) are a rich representation language for structured statistical models. They combine a frame-based logical representation with probabilistic semantics based on directed graphical models (Bayesian networks). This chapter gives an introduction to probabilistic relational models, describing semantics for attribute uncertainty, structural uncertainty, and class ...

Traditional approaches to interpretation in natural language processing typically fall into one of three classes: syntaxdriven, semantics-driven, or frame/task based. Syntaxdriven approaches use a domain-independent grammar to drive the interpretation process and produce a global parse of the input, accounting for each word of the sentence. Semantics-driven approaches use knowledge about the ca...

In this paper we investigate minimal semantics for First Order Dynamic Logic formulas The goal is to be able to write action speci cations in a declarative pre post condition style The declarative speci cation of actions comes with some well known problems the frame problem the quali cation problem and the ram i cation problem We incorporate the assumptions that are inherent to both the frame a...

In this paper five levels of specification of nonmonotonic reasoning are distinguished. The notions of semantical frame, belief state frame and reasoning frame are introduced and used as a semantical basis for the first three levels. Moreover, the semantical connections between the levels are formalized. It is shown that this general semantical framework is applicable for some well-known approa...

Probabilistic relational models (PRMs) are a rich representation language for structured statistical models. They combine a frame-based logical representation with probabilistic semantics based on directed graphical models (Bayesian networks). This chapter gives an introduction to probabilistic relational models, describing semantics for attribute uncertainty, structural uncertainty, and class ...

One of the modern paradigms to develop an application is object oriented analysis and design. In this paradigm, there are several objects and each object plays some specific roles in applications. In an application, we must distinguish between procedural semantics and declarative semantics for their implementation in a specific programming language. For the procedural semantics, we can write a ...

We develop an abstract theory of justifications suitable for describing the semantics of a range of logics in knowledge representation, computational and mathematical logic. A theory or program in one of these logics induces a semantical structure called a justification frame. Such a justification frame defines a class of justifications each of which embodies a potential reason why its facts ar...

We introduce a new order-topological semantics for the positive modal mu-calculus over modal compact Hausdorff spaces, which are generalizations of descriptive frames. We define Sahlqvist sequents in this language, prove Esakia’s lemma and Sahlqvist preservation theorem for this semantics. We show that every Sahlqvist sequent has a frame correspondent in first-order logic with fixed-point opera...

1 We consider the semantics of predicate Kripke frames with equality (called I-frames, for short), which is equivalent to the semantics of Kripke sheaves (see [3]). Namely, a (predicate) Kripke frame is a pairM = (W,U) formed by a posetW with the least element 0W and a domain map U defined on W such that U(u)⊆U(v) for u≤v. An I-frame is a triple M = (W,U, I), in which (W,U) is a Kripke frame an...