On compositional modelling

Abstract

Many solutions to AI problems require the task to be represented in one of a multitude of rigorous mathematical formalisms. The construction of such mathematical models forms a difficult problem which is often left to the user of the problem-solver. This void between problem-solvers and their problems is studied by the eclectic field of automated modelling. Within this field, compositional modelling, a knowledge-based methodology for system-modelling, has established itself as a leading approach. In general, a compositional modeller organises knowledge in a structure of composable fragments that relate to particular system components or processes. Its embedded inference mechanism chooses the appropriate fragments with respect to a given problem, instantiates and assembles them into a consistent system model. Many different types of compositional modeller exist, however, with significant differences in their knowledge representation and approach to inference. This paper examines compositional modelling. It presents a general framework for building and analysing compositional modellers. Based on this framework, a number of influential compositional modellers are examined and compared. The paper also identifies the strengths and weaknesses of compositional modelling and discusses some typical applications.

Use-Misuse Case Driven Analysis of Positive Train Control

“…While considerable research has focused on using decision support systems to reason about evidence [7,15,22] and on generating crime scenarios from evidence using compositional reasoning [16], we believe that our use of use-misuse cases to determine the forensic evidence that should be collected for determining safety and security requirements is unique. The systematic analysis of forensic evidence from misuse cases proposed in this work will not only support accident investigations and contribute to the identification and prosecution of attackers, but will also increase the resilience of PTC systems to attack.…”

Intelligent Hybrid Control Model for Lighting Systems Using Constraint-Based Optimisation

“…We assume that we can create/redesign a system-level model by composing components from a component library [ [4], [5]]. We call a well-defined model fragment a component.…”

Granularity and disaggregation in compositional modelling with applications to ecological systems

“…It includes abductive compositional modellers [16] that search for a structural scenario for a system whose predicted behaviour matches observed behaviour. Readers interested in a detailed discussion of the tasks solved by other types of compositional modeller and how they are related to automated modelling approaches in general are referred to [20] for a detailed overview.…”

“…However, these models of individual phenomena can be composed into models describing the combined effect of different phenomena. Therefore, compositional model repositories employ a knowledge base that contains descriptions of partial models, called model fragments [9,20], and they possess inference mechanisms that search for ways to combine these partial models with regard to a given scenario. The partial models described by the model fragments can not be composed arbitrarily, however.…”