=Paper=
{{Paper
|id=Vol-1701/paper3
|storemode=property
|title=Revisiting Workflow Interactions for Petri Net-Based Agents (Extended Abstract)
|pdfUrl=https://ceur-ws.org/Vol-1701/paper3.pdf
|volume=Vol-1701
|authors=Thomas Wagner,Daniel Moldt
|dblpUrl=https://dblp.org/rec/conf/emisa/WagnerM16
}}
==Revisiting Workflow Interactions for Petri Net-Based Agents (Extended Abstract)==
https://ceur-ws.org/Vol-1701/paper3.pdf
Jan Mendling and Stefanie Rinderle-Ma, eds.: Proceedings of EMISA 2016,
Gesellschaft für Informatik, Bonn 2016
Workflow Management Principles for Interactions Between
Petri Net-Based Agents (Extended Abstract)
Thomas Wagner1 Daniel Moldt1
Abstract: Agents provide suitable mechanisms for modelling complex interactions in distributed
systems. In some cases, though, classical agents interactions may exhibit issues of complexity and
rigidness. These issues can lead to cumbersome and inefficient implementations. Introducing work-
flow and especially task principles into agents interactions extends the mechanisms available to
agent modellers. With these improved mechanisms it is possible to avoid issues found in classical
agents interactions. This contribution describes a Petri net-based approach on this topic. The work
summarised in this extended abstract has been published in [WM15b].
Keywords: Workflows, Agents, Integration, Interaction, Communication, Petri Nets
1 Introduction
Agents interactions provide the means to design, model and implement complex relations
between components (i.e. agents) in distributed systems. Agents interaction patterns are
usually highly complex and describe which agents are exchanging what data at what pre-
cise point in their execution. The ability to model this complexity is beneficial for most
scenarios. However, the strict association of specific agents or roles of agents to particular
data and/or functionality also contains an inherent rigidity. Especially in an open system,
agents with capabilities unknown beforehand may be available. Incorporating these agents
into a system is challenging, due to the rigidly defined interactions.
One approach to solve and avoid these kinds of issues originates from the field of work-
flow management. Agents interacting to provide the functionality within a system are con-
ceptually very similar to humans doing work facilitated by a workflow. Both, agents and
humans, serve as resources to a set of related processes. These processes consist of tasks
that need to be accomplished in order for the process to finish. For agents as resources,
these tasks are usually implicit within their behaviour. At some point during execution
they receive a message and react to it by performing the pre-defined behaviour. Another
difference is that there is no separate and explicit workflow or workflow engine(s) present
in an agent system. Instead, the agents themselves serve as the engines whenever they re-
quest work from other agents. Altogether, this means that agents serve as both workflow
resources and workflow engines within an agent system considered in workflow terms. The
approach described in this abstract implements this idea to improve agents interactions.
This extended abstract is structured as follows: After this introduction the overall approach
is presented in Section 2, a prototype in Section 3 and the abstract concludes in Section 4.
1 University of Hamburg, Department of Informatics, http://www.informatik.uni-hamburg.de/TGI/
2 Approach
The general approach takes the perspective that an agent system is a workflow system
with a specialised form and categorisation of components. The behaviour of and between
agents is considered in the form of workflow processes modelled as workflow Petri nets
[vdA97]. These processes partition the functionality within the behaviour into explicitly
modelled tasks. Tasks are intended to be executed by any agent that features the required
functionality. The interface to the tasks is kept as generic as possible, simply requiring the
form of input and output/result data. Task parameters describe the required functionality
for the task as well as data formats. The understanding of the task concept follows the idea
of the task transition [Ja02] for reference Petri nets [Ku02].
Figure 1 gives an overview of the approach. Some agents initiate, control and manage
parts of the behaviour (i.e. the workflow processes) of a system. In workflow terms these
agents act as workflow engines. Whenever a task becomes available, the information about
it is sent to the so-called intermediary system. The intermediary system is a subsystem
of agents providing standardised functionality. In workflow terms the intermediary system
serves a function similar to a workflow enactment service (cf. [Ho95]). It gathers the infor-
mation about available tasks from all engines and forwards it to the appropriate resources.
Any agent of the system is a potential resource and registers itself and its capabilities with
the intermediary system. The intermediary system filters available tasks for resources ac-
cording to their capabilities. Resources can decide to request the tasks offered to them.
When that happens the request is routed via the intermediary system to the engine. Note,
that all communication between engines and resources happens with the involvement of or
via the intermediary system. The engine has autonomous control over its workflows and
can decide whether to agree to the request or not.
Fig. 1: Overview of the Approach (Edited from [WM15b])
Jan Mendling and Stefanie Rinderle-Ma, eds.: Proceedings of EMISA 2016,
Gesellschaft für Informatik, Bonn 2016
If it agrees, the request transitions in all three components fire (conceptually2 ) synchro-
nised (upper part of Figure 1). The resource then uses its internal functionality to execute
the work associated with the task. If at any point the engine or the resource decide to can-
cel the task execution, the cancel transition in all three components is synchronised. If the
resource is finished, it informs the engine of the result, but the engine has control whether
or not to accept the result (or to cancel the task). Accepting the result confirms the task
and fires and synchronises the corresponding confirm transitions in all three components.
The main effect of the approach is a decoupling of agents as interaction partners. Engines
do not need to know beforehand which other agent is capable of and available to execute
their requests. Agents simply send the task information to the intermediary system, which
forwards it to all eligible resources. In cases of high workload the intermediary system may
(in e.g. an open system) consider alternative resources and evaluate their functionality for a
task. The benefits of the decoupling are increased flexibility and efficiency. There are also
some disadvantages, especially w.r.t. the centralised nature of the intermediary system.
These issues can mostly be solved in the implementation.
3 W ORK B ROKER-Prototype
The approach described above has been implemented in the W ORK B ROKER-prototype.
The W ORK B ROKER realises an intermediary system using M ULAN (Multi-Agent Nets,
[Rö04]) and C APA (Concurrent Agent Platform Architecture, [DMR03]) agents. It is inte-
grated as a proof of concept into our software development support system (S DCC) for the
PAOSE approach (Petri net based, Agent- and Organization-oriented Software Engineer-
ing3 ). Agents (as engines) representing development teams execute development work-
flows. Tasks are e.g. requests for other development teams to fix bugs, change a common
interface or clarify design choices. The engines create these tasks and send the information
to the W ORK B ROKER intermediary system, which forwards them to the affected other de-
velopment team agents. These agents then serve as the resources for the tasks with the
W ORK B ROKER handling communication and management of the interactions.
4 Conclusion
In conclusion, the approach presented in this abstract enhances the way agents interact
and cooperate. Utilising the idea of agents as engines as well as resources and considering
interactions as (parts of) tasks and workflows allows modellers to exploit the advantages
of workflows regarding behaviour modelling. It does not limit or prohibit any options re-
garding classical agents interactions and is thus a straightforward extension of capabilities
for modellers. One can flexibly choose the best mechanism for each interaction.
In fact, the approach brings the concepts agents and workflows closer together. It is part of
larger, ongoing work to combine and integrate the concepts of agent and workflow on the
2 Actual implementations would only enact a pseudo-synchronisation within distributed settings.
3 see http://www.paose.de
abstract level. Through such an integration, the strengths of both, agents and workflows,
can be made available to system modelling. Introducing workflow principles into agent
behaviour is an important step for this integration. More information about the overall
work on the integration can be found in [WM15a].
Applying the agent/workflow approach to our own S DCC provides relevant insights into
the complex but powerful mechanisms: Currently, a new version of the W ORK B ROKER is
being implemented in the prototype for the overall integration of agents and workflows.
This new W ORK B ROKER realises an intermediary system between entities that can dy-
namically act and be regarded as agents, workflows or both. These entities are used for
modelling systems in which structural and behavioural modelling abstractions are consid-
ered equally. The new prototype not only considers agents interactions in workflow terms,
but instead the entirety of the agent. Using these integrated entities makes it easier and
more directly possible to exploit workflow principles for agents. The effects are currently
being researched, but are, from a modelling point of view, very promising.
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