Abstract
To achieve more widespread application, workflow systems need to be developed to operate in dynamic environments
where they are expected to ensure that users are supported in performing flexible and creative tasks while maintaining
organisational norms. We argue that in order to cope with these demands, the systems must be provided with knowledge
about the organisational structure and authority context of tasks. We support this argument by identifying a number
of decision points that an adaptive workflow system must support, discussing how these decisions can be supported
with technically oriented capability specifications, and describe how this support can be enhanced with the inclusion
of knowledge about organisational structure and authority. We outline how such knowledge can be captured, structured,
and represented in a workflow system. We then demonstrate the use of such knowledge by describing how the task initiation, task planning, activity scheduling, and agent interaction functions within a workflow system can be
enhanced by it.
58K gzipped ps file
AIAI-TR-232 "A Framework for Equipping Workflow Systems with Knowledge about Organisational Structure and Authority."; Peter Jarvis, Jussi Stader, Ann Macintosh, Jonathan Moore, and Paul Chung; in Proceedings of the Workshop on Systems Modeling for Business Process Improvement (SMBPI-99), University of Ulster, County Antrim, Northern Ireland, UK, March 1999. Also to appear in a book published by Arthouse in late 1999; £4.00 UK/surface mail; £6.00 airmail.
Abstract
To achieve more widespread application, workflow systems need to be developed to operate in dynamic environments where they are expected to ensure that users are supported in performing flexible and creative tasks while maintaining organisational norms. We argue that in order to cope with these demands, the systems must be provided with knowledge about the organisational structure and authority context of tasks. We support this argument by identifying a number of decision points that an adaptive workflow system must support, discussing how these decisions can be supported with technically oriented capability specifications, and describe how this support can be enhanced with the inclusion of knowledge about organisational structure and authority. We outline how such knowledge can be captured, structured, and represented in a workflow system. We then demonstrate the use of such knowldge by describing how the task initiation, task planning, activity scheduling, and agent interaction functions within a workflow system can be enhanced by it.
Abstract
Early work on the NONLIN and O-Plan projects indicated a need for a
defined methodology which would guide users performing various roles in the
acquisition and analysis of domain requirements for planning. This work
included links to a requirement analysis methodology, CORE (COntrolled
Requirements Expression), tool support via an intelligent assistant as part
of the Task Formalism (TF) Workstation and an initial collection of
guidelines and checklists to aid in using the TF domain description
language. This paper describes work underway to follow-on from this past
research and to infuse it with knowledge gained from recent research related
to planning domain development, knowledge modelling, design rationale and
ontological and requirements engineering.
Abstract
In this paper we describe how we are exploiting AI technologies to
infuse workflow systems with adaptive capabilities. This work is part of an
ongoing applied research programme between AIAI and a number of industrial
and academic partners. We begin by presenting the requirements of adaptive
workflow within a taxonomy consisting of the layers of domain, process,
agents, organisation, and infrastructure. We then show how each level can be
substantially addressed with AI technologies. Specifically, infrastructure
adaptation is addressed with multi-agent toolkits, agent adaptation through
knowledge-based capability matching, organisational adaptation through
authority based capability matching, process adaptation through AI planning
and execution architectures, and domain adaptation through rationale
capture. We conclude by identifying important challenges for further work as
being the improvement of rationale capture and the support for the evolution
of the process models that underlie executing processes.
Abstract
The AllDay Financial Services Group has the stated business goal of
being able to sell any of its products, at any time of the day or night, in
any place, and through any available channel to market. In this paper, we
outline the business benefits this Group has obtained from the deployment of
current workflow technology and short comings of the technology that are
preventing the Group from completely satisfying its business goal. We then
set out the research issues raised by this experience and discuss how
emerging AI technologies could be exploited in satisfying them. The AI
technologies discussed include information-gathering planning, general
planning, and scheduling. We conclude by encouraging the formation of
partnerships between workflow users, workflow vendors and AI researchers.
Such partnerships will give researchers access to real problems that can be
used to demonstrate the scalability of their work and provide evidence that
will encourage vendors and users to exploit the technologies. The feed back
will also guide researchers on where further research should be focused.