Putting Expectations in Order

Putting order in risk measures

This paper introduces a set of axioms that define convex risk measures. Duality theory provides the representation theorem for these measures and the link with pricing rules. 2002 Published by Elsevier Science B.V. JEL classification: G11; G12; G13

Higher Order Expectations

We study higher-order expectations paralleling the Harsanyi (1968) approach to higher-order beliefs—taking a basic set of random variables as given, and building up higher-order expectations from them. We report three main results. First, we generalize Samet’s (1998a) characterization of the common prior assumption in terms of higher-order expectations, resolving an apparent paradox raised by h...

Violating expectations of color order

Putting order to the separation logic jungle

Research results from so-called “classical” separation logics are not easily ported to so-called “intuitionistic” separation logics, and vice versa. Basic questions like, “can Brookes’s soundness proof of CSL be extended to intuitionistic separation logics?” “Can the frame rule be proved independently of whether the programming language is garbage-collected?” “Can amortized resource analysis be...

Putting OWL in Order: Patterns for Sequences in OWL

Sequences are a natural part of the world to be modelled in ontologies. Yet the Web Ontology Language, OWL, contains no specific support for ordering. It does, however, have constructs that can be used to model many aspects of sequences, albeit imperfectly. This paper demonstrates a design pattern for modeling order within OWL-DL. This allows us to use standard DL reasoning to perform pattern m...