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Department of Computer Science

Empirical Modelling for Concurrent Systems: an overview

Conceiving and developing a concurrent system entails assembling physical objects / agents, establishing a regime for observation and protocols for interaction. Subject to reliable operation (an assumption about the environment), we then have generic patterns of state change (behaviours) that fulfil expectations. Empirical Modelling is concerned with principles and tools that can be used to identify and construct concurrent systems. (To be ilustrated using the Railway Animation model.)

Construing a concurrent system involves accounting for system behaviours by identifying agents / objects and the observables that mediate their interaction (cf. an LSD account). This construal typically draws on a vast amount of experience: personal, of natural phenomena, of social interaction. The issues raised concern knowledge that migrates in many different ways: from subjective to objective, particular to general, provisional to assured. (To be illustrated by LSD examples, railway accident scenarios and models.)

The knowledge representation entailed in this construal cannot be propositional in character. Formal specification of intended system behaviour and/or system components - by itself - has only a very limited role to play. Empirical Modelling advocates knowledge representation based on the open and interactive development and use of (typically computer-based) artefacts.  (To be illustrated using the Digital Watch model.) The principles and techniques involved in this development resemble those of experimental science and engineering. In Empirical Modelling, interaction with computer-based artefacts is used to generate experiences that metaphorically represent other experiences of our own, and the "experiences" we project on to other agents in an LSD account. (To be illustrated using the Ant Navigation model.)

Resources for tackling the above agenda ...

Lecture notes

Background lectures on Empirical Modelling for concurrent systems amplifying the above summary can be found at the following links:

Selected topics from these lectures will be discussed, primarily with reference to specific models and exercises. They may be useful for reference, but you will NOT be expected to be familiar with all these lectures!

Models