Multi-state models provide a unified framework for the description of the evolution of discrete phenomena in continuous time. One particular example are Markov processes which can be characterised by a set of time-constant transition intensities between the states. In this paper, we will extend such parametric approaches to semiparametric models with flexible transition intensities based on Bay...

I construct a multi-agent state space model with unawareness following Aumann (1976). Dekel, Lipman and Rustichini (1998) show that standard state space models are incapable of representing unawareness. The model circumvents the impossibility result by endowing the agent a subjective state space that differs from the full state space when he has the unawareness problem. Information is modeled a...

This paper continues the line of research on the representation and compilation of propositional knowledge bases with propositional directed acyclic graphs (PDAG), negation normal forms (NNF), and binary decision diagrams (BDD). The idea is to permit variables with more than two states and to explicitly represent them in their most natural way. The resulting representation languages are analyze...