=Paper=
{{Paper
|id=None
|storemode=property
|title=A Goal Based Approach on top of Petri Nets
|pdfUrl=https://ceur-ws.org/Vol-723/paper14.pdf
|volume=Vol-723
|dblpUrl=https://dblp.org/rec/conf/apn/SaadallahD11
}}
==A Goal Based Approach on top of Petri Nets==
https://ceur-ws.org/Vol-723/paper14.pdf
A Goal Based Approach on top of Petri Nets
Nejm Saadallah and Benoit Daireaux
IRIS 4068 Stavanger Norway nejm.saadallah@iris.no , IRIS 4068 Stavanger Norway
benoit.daireaux@iris.no
Abstract. This poster presents ongoing work and mainly proposes a
way to model goals on a Petri net model. We consider that the basic
functioning of many machines can be captured in a Petri net model, while
the environment where the machine is deployed is often too complex to
be modelled in Petri nets. We handle the influence of the environment
on the choice of operations by the so-called external agents, and show
how these agent’s goals could be studied before real deployment.
Keywords: Control System, Agents, Supervisory Control, Petri Net,
Model building
1 Problem Formulation
The basic idea of our approach is to use Petri nets [6] to model the dynamic of
machines [1, 3, 5, 4], regardless of the environments in which they are deployed,
and use the notion of agents’goals to model the influences of the environments
on the machine’s behaviour. Our approach is motivated by two facts. The first
fact is that basic functioning of many machines can be captured in a Petri net
model. The second fact is that the environments in which a given machine is
deployed are often hard to model within Petri nets. In contrast with synchronous
Petri nets [2] which include sensory data into transition firing rules, we consider
sensory data as inputs to external agents that need to interact with the machine.
Fig. 1. Actions are chosen ac-
cording to a logic control that
is captured using the concept
of control interpreted Petri nets.
The machine commands affect
the surrounding environment,
which is reflected in sensory
data. An external agent could
be a software or human agent
continuously analyses sensory
data, and triggers actions.
194 PNSE’11 – Petri Nets and Software Engineering
In this work we are interested in finding a systematic approach for studying
the behaviour of agents, based on their respective goals. Given a set of agents
acting on a machine that is modelled in Petri net, how can we classify the
behaviour of these agents? To the system designer, this approach is intended to
give an understanding of the system prior to its implementation. Modelling the
execution policy, that is, how the interaction between the agents and the Petri
net model could be implemented is not addressed in this paper, but is shortly
discussed in Section 3.
2 Modelling Goals
Fig. 2. Shows a simple elevator en-
hanced with 5 agents. Light mainte-
nance agent will trigger every period
of time to check whether the light lamp
is still working or not. Elevator dis-
abling agent will trigger if there is a
fire in the building and no person in
the elevator, to keep the door closed.
Goods delivery agent moves the el-
evator to the floor 0. VIP agent re-
quests the elevator to be at the third
floor with the door open. Air con-
ditioning agent, when triggered the
door of the elevator stays open for a
period of time.
The five agents shown in Figure 2, are categorised according to four relations
as illustrated in Table 1. The four relations are defined as follows:
Distinctly Inclusive goals: We say that a goal ga distinctly includes gb if by
achieving ga , gb is also achieved.
Mutually Inclusive goals: We say that two goals ga and gb are mutually
inclusive if ga distinctly includes gb , and gb distinctly includes ga .
Partially Inclusive goals: We say that ga partially include gb , when only some
markings that achieve ga also achieve gb but not all of them.
Mutually Exclusive goals: We say that two goals ga and gb are mutually
exclusive when they can not be achieved together.
3 Conclusion and Future Work
In this paper we have addressed some aspects that are related to machines de-
ployed in complex environments. We believe that the basic functioning of many
N. Saadallah and B. Daireaux: A Goal Based Approach on top of Petri Nets 195
Table 1. Summary of the relations between the five goals of Figure 2
Goals Mutual Mutual Distinct Partial
Exclusion Inclusion Inclusion Inclusion
Light maintenance g1 g4 , g5 g2 g2 g3 via M1
Elevator disabling g2 g4 , g5 g1 g1 g3 via M1
Goods delivery g3 g4 No No g5 via M0 , g1
and g2 via M1
VIP g4 g1 ,g2 ,g3 No g5 No
Air conditioning g5 g1 ,g2 No No g3 via M0 , g4
via M7
machines can be captured in a Petri net model, while the environments where
the machines are deployed are often too complex to model in Petri nets. We con-
sider that the influence of the environment on the machine is handled by agents,
and raise the the following question: how agents acting on a machine can be cat-
egorised? We answer the question by introducing four properties, and use these
properties to analyse some behavioural aspects, prior to system implementation
as illustrated in Table 1.
We focused on the off-line analyses of agents acting on a machine, but we
have not studied the on-line problematic, in other words the execution policy.
When several agents are involved, which one should have the priority to execute?
Another interesting question would be to find the set of necessary agents that
guaranty some safety levels. To be more precise, could we provide a Petri net
modelled machine with a set of safety agents, such that even in the presence of
other faulty agents, the system guaranties the specified safety level? We believe
that this work could be done within the Petri net formalism, and will be the
subject of our future efforts.
References
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systems. 2006.
2. René David and Hassane Alla. Discrete, Continuous, and Hybrid Petri Nets.
Springer, 1 edition, November 2004.
3. B. Hrz and M. C. Zhou. Modeling and Control of Discrete-event Dynamic Systems:
with Petri Nets and Other Tools. Springer Publishing Company, Incorporated, 2nd
edition, 2007.
4. Vedran Kordic, editor. Petri Net, Theory and Applications. I-Tech Education and
Publishing, 2007.
5. Tadao Murata. Petri nets: Properties, analysis and applications. pages 541–580,
April 1989. NewsletterInfo: 33Published as Proceedings of the IEEE, volume 77,
number 4.
6. Carl Adam Petri. Communication with automata. PhD thesis, Univ. Hamburg,
1966.