The problem we have addressed in this dissertation is that of designing a pragmatic
framework for integrating the synthesis and management of organisational process
knowledge which is based on domain-independent AI planning and plan representations. Our solution has focused on a set of framework components which provide
methods, tools and representations to accomplish this task.In the framework we address a lifecycle of this knowledge which begins with a
methodological approach to acquiring information about the process domain. We show
that this initial domain specification can be translated into a common constraint-based
model of activity (based on the work of Tate, 1996c and 1996d) which can then be
operationalised for use in an AI planner. This model of activity is ontologically underpinned and may be expressed with a flexible and extensible language based on a
sorted first-order logic. The model combines perspectives covering both the space of
behaviour as well as the space of decisions. Synthesised or modified processes/plans can
be translated to and from the common representation in order to support knowledge
sharing, visualisation and mixed-initiative interaction.This work united past and present Edinburgh research on planning and infused it
with perspectives from design rationale, requirements engineering, and process knowledge sharing. The implementation has been applied to a portfolio of scenarios which
include process examples from business, manufacturing, construction and military operations. An archive of this work is available at: http://www.aiai.ed.ac.uk/~oplan/cpf
