In this paper a compositional verification method for models of knowledge-based systems is introduced. Required properties of the system are formally verified by deriving them from assumptions that themselves are properties of sub-components, which in their turn may be derived from assumptions on sub-sub-components, and so on. The method is based on properties that are formalised in terms of te...

Although Aitchison’s [Aitchison, J., 1986. The Statistical Analysis of Compositional Data, Chapman and Hall, London] method of logratio transformation of compositional data is widely used in various domains, it is limited by the assumption of a strict non-negativity of the components and the requirement of special treatments in practice of the zero components. We propose a dimension-reduction a...

We improved the compositional term translation method by using comparable corpora. A bilingual lexicon consisting of pairs of word sequences within terms and their correlations is derived from a bilingual document-aligned corpus. Then, for an input term, compositional translations are produced together with their confidence scores by consulting the corpus-derived bilingual lexicon. Thus, we can...

Complex interactions among the meanings of words are important factors in the function that maps word meanings to phrase meanings. Recently, compositional distributional semantics models (CDSM) have been designed with the goal of emulating these complex interactions; however, experimental results on the effectiveness of CDSM have been difficult to interpret because the current metrics for asses...

6 Compositional specification of a forest landscape model using CPDPs 34 6.

I have investigated systems for on-line, cumulative learning of compositional hierarchies embedded within predictive probabilistic models. The hierarchies are learned unsupervised from unsegmented data streams. Such learning is critical for long-lived intelligent agents in complex worlds. Learned patterns enable prediction of unseen data and serve as building blocks for higherlevel knowledge re...

We present a new technique for automatically synthesizing the assumptions needed in compositional model checking. The compositional approach reduces the proof that a property is satisfied by the parallel composition of two processes to the simpler argument that the property is guaranteed by one process provided that the other process satisfies an assumption A. Finding A manually is a difficult ...

In this paper we detail our effort to formalize and prove requirements for the Quad-redundant Flight Control System (QFCS) within NASA’s Transport Class Model (TCM). We use a compositional approach with assume-guarantee contracts that correspond to the requirements for software components embedded in an AADL system architecture model. This approach is designed to exploit the verification effort...

Categorical compositional distributional semantics is a model of natural language; it combines the statistical vector space models of words with the compositional models of grammar. We formalise in this model the generalised quantifier theory of natural language, due to Barwise and Cooper. The underlying setting is a compact closed category with bialgebras. We start from a generative grammar fo...

Probabilistic compositional models, similarly to graphical Markov models, are able to represent multidimensional probability distributions using factorization and closely related concept of conditional independence. Compositional models represent an algebraic alternative to the graphical models. The system of related conditional independencies is not encoded explicitly (e.g. using a graph) but ...