Journal of Software Engineering and Applications, 2013, 6, 14-22
http://dx.doi.org/10.4236/jsea.2013.69A002 Published Online September 2013 (http://www.scirp.org/journal/jsea)
APN Model for Specification of the Communication
Protocols in Multi-Agent System
Marzougui Borhen1, Kamel Barkaoui2, NejibBen Hadj Alouane3
1Emirates College of Technology, Abu Dhabi, UAE; 2Nationnal des Arts et Métiers, Paris, France; 3OASIS, National Engineering
School of Tunis, Tunis, Tunisia.
Received June 15th, 2013; revised July 18th, 2013; accepted August 26th, 2013
Copyright © 2013 Marzougui Borhen et al. This is an open access article distributed under the Creative Commons Attribution Li-
cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
This paper deals with the proposal of a new model based on Agent Petri Nets (APN) to specify interactions among
agents in Multi Agents System (MAS). Indeed, an agent approach requires a powerful and expressive formalism that
allows him to model the behavior of a set of ag ents that interact. We are modeling some variants of FIPA standard pro-
tocols. Our Models are found b ased on communicating co gnitive agents. Each Agent is capable of perceiving th eir en-
vironment partly and building, sending and receiving messages.
Keywords: Model; AP; MAS; formalism; Interact; FIFA; Protocols
1. Introduction
The basic function of an interaction protocol is to provide
a way for agents to communicate effectively without
having to explicitly plan for each speech act by delimit-
ing the space of possible answers [1]. When using an
interaction protocol, we assume that, during analysis, it
must be made to ensure that following the protocol will
achieve the goals associated with final states. Protocol is
more efficient with less information which needs to be
transmitted, and less time is spent in communication. All
agents attend different interact protocols appropriately
between them, for example, responding to message, per-
forming actions in their respective fields, or updating
their local states. So, protocols can be taken as a way to
specify the policy that agents will follow in their interac-
tions with others [2]. This policy will determine the con-
ditions under whi c h a request can be satis fi ed.
Sometimes, when a problem solved by two or more
modules it becomes quite complex. The protocol de-
scribes the communication will. This has led researchers
to propose protocol engineering, specify properties that a
protocol should satisfy and provide multiple modeling
formalisms. This is to simplify the representation of com-
munication protocols.
The definition of generic software architecture for in-
teroperability among agents in a dynamic environment
seems to be interesting for the operation of these proto-
cols.
Indeed, several research groups have developed their
own models such as General Magic, KAOS, OMG, ZEUS
and FIPA, which have defined an environment of exis-
tence and operation of agents and a platform that describes
the agents, their creation, and deletio n authentication.
In this context, we involve formal specifications me-
thods to describe some complex properties of engineer-
ing protocols. We focus in this work on modeling inter-
action between agents and Agents Petri Nets (APN) [3-5].
Indeed, the complementarity between Multi Agent Sys-
tem (MAS) and APN becomes very advantageous: an
approach by agents requires a powerful and expressive
formalism that allows him to model the behavior of a set
of agents that interact.
This paper is organized as follows: Section 2 describes
the interaction between the agents; Section 3 relies on
interaction protocols. We propose in Section 4 our inter-
action models based on APN and MAS. In the last sec-
tion we conclude this paper by giving some perspectives.
2. Interaction between Agents
The interaction, with the organization, is one of the basic
concepts of multi-agent systems. According to [6], “for
an agent, interact with one another is both the source of
his power and the source of his problems”. Indeed, it is
the cooperation of agents who brings a kind of intelli-

APN Model for Specification of the Communication Protocols in Multi-Agent System 15
gence or ability to solve problems rather complex, but
also because of their many conflicts that arise.
The concept of interaction is the basic issues in MAS
since it is thanks to it that the agents will be able to pro-
duce complex collective behaviors and dependent on
each other. We call interaction situation a set of behav-
iors resulting from the whole of agents that must act to
meet their objectives within the constraints of resources
from more or less limited and they have their individual
skills. We provide a classification of interaction situa-
tions according to several criteria:
 The presence of common objective,
 Access to shared resources,
 The distribution of skills within MAS.
The interaction can also match th e ways in which these
linkages between entities take place within the system.
Based on these criteria and the objective of the system,
the interaction may be direct or indirect.
2.1. Indirect Interaction
The Interaction is described as indirect if it is not ad-
dressed explicitly to another agent. But it is achieved by
the environment which tracks of the interaction between
all agents [7]. The agents involved in this interaction are
the agents who perceive these changes in the environment.
Thus, an agent performing an indirect interaction is not
sure how other agents with which it is about to interact as
agent does not know what will have to change their be-
havior by observing the changes in the environment as
shown in Figure 1.
2.2. Direct Interaction
Interaction is direct if it is precise [8] and directed ex-
plicitly to a recipient (an agent or group of agents) in
order to modify its behavior (or internal state) [7]. The
direct interaction based on message (information ex-
change) sending between agents. This action is deter-
mined by the laws of behavioral agents as shown in Fig-
ure 2.
Depending on the types of agents involved direct inter-
action can also take many forms. This can be expressed
for using reagents exchange of simple signals (as in the
case of the eco-resolution) and cognitive agents, using
language and communication protocols developed. It is
inspired by social interaction (communication between
humans) and supports a vision of the interaction and high
communication [9]. Thus, researches in MAS consider
that communication models are more complex, like the
philosophy of l a nguage.
3. Interaction Protocols
Address the problem of interaction in the field of SMA is
to provide the means to analyze and design the various
Figure 1. Indirect interaction between agents.
Agent1
Ag ent2
A
g
e
nt3
Ag ent4
message
message
message
message
message
message
Figure 2. Direct interaction by sending messages between
agents.
forms of interaction that agents can use to accomplish
their tasks and fulfill their go als. So, the solutions consist
to assure an interacti on pr ot ocol s.
An interaction protocol is a set of rules that govern the
communication between several agents [1]. It allows to
describe explicitly conversational sequences when the
interaction between agents (who can say what to whom
and when). These protocols are used to define a sequence
of messages communicated between agents and describe
how agents should react to messages received during in-
teractions [10]. For a given state of the protocol, there are
a finite number of messages in transmission and recap-
tion.
If an agent agrees to use a protocol then he agrees to
comply with this protocol and to abide by its syntax and
semantic rules (on the architecture of the protocol defin-
ing the actions that agents must perform when sending
and receiving a message).
3.1. Types of Interaction Protocols
Interaction protocols can be classified according to the
types of agents (coo perative, competitive or shared goals)
[11].
3.1.1. C o ordination Protocols
They enable agents to manage (maintain, adjust or aban-
don) their commitments in cases where the circumstances

APN Model for Specification of the Communication Protocols in Multi-Agent System
16
in which they were developed, evolve. Among coordina-
tion protocols include acquaintance networks for distrib-
uted task allocation and Contract Network. The major
advantage of the latter is that it allows the coordination
of tasks between the agents who are ensuring the most
possibl e o ptimal al location.
3.1.2. Cooperation Protoc ols
Cooperation protocols consist to decompose tasks into
subtasks and distribute them among different agents
specifying who does what, with what resources, for what
purposes and under what constraints. This strategy aims
to reduce the complexity of tasks and optimize resource
utilization. There are various mechanisms for allocating
tasks such as election where tasks are assigned pursuant
to an agreement or a vote.
3.1.3. Nego ti a tion Protoc ol s
Negotiation protocols are used in the case where agents
have different goals or the use of a resource by agents
can prevent another agent to achieve its goal. The proto-
col followed in the negotiation and decision-making
process that determines each agent uses its positions and
criteria for agreement [12].
3.2. FIPA Protocols
FIPA [13] provides the description of a set of protocols
for high-level interaction, including the request for action,
establishing contract (Contract Net) and several types of
auctions.
Basic Protocols
These protocols are often used and implicitly. They are
listed in [13] and specified in the ACL. They allow an
agent to simply ask another to perform an action (request
protocol) to request information (query protocol), etc. In
the following we mention some of them:
The FIPA Request Protocol: This protocol allows an
agent to request another agent to perform a certain action
as shown in Figure 3. The officer receiving the request
shall, upon receipt thereof, indicate whether it accepts or
rejects the request. The agent accepts the request must
also notify the applicant when the action concerned by
the request is made.
a) Conditional query protocol FIPA: This protocol al-
lows an agent to request another agent to perform an ac-
tion when a certain condition is met. The agent accepts
the request must wait until the condition is met to per-
form the requested action. It must then inform the initia-
tor of the request that the action was performed.
b) The FIPA request protocol: It allows an agent to
make an inquiry. The officer receiving the request can
then accept or refuse to provide information. It must of
Figure 3. AUML Representation of protocol FIPA query
[13].
course give the requested information if it accepts the
request.
3.3. Network Protocols Contractual FIPA
This protocol specifies how to use the sharing protocol
tasks Contract Net [14] using FIPA-ACL as a language
of communication. This protocol allows an agent (the
manager or originator in Figure 4.) To make a bid for
performed job, agents who wish to carry out the task in
question (or participants) must provide their services.
Depending on the offers received, the manager decides to
whom he attributes the accomplishment of the task. In
fact, it determines which agent is awarded the contract
for completion of the task. Finally, the agent who gets
the contract must inform the manager when the task is
completed.
3.4. Protocols FIPA Auction
Protocols of this family are widely used in the field of
electronic commerce. It generally refers to two different
versions of auction protocols which are English and
Dutch.
a) Protocol FIPA Dutch Auction: In a Dutch auction,
the seller sets a starting price that is far beyond the actua l
value of the property that is for sale. Then the price is
reduced until a buyer accepts announces that the pro-
posed price. The property is then sold to the purchaser.
b) The English auction protocol FIPA: This protocol
(Figure 5.) allows an agent to u se an auction to sell type
English property. The seller sets a starting price that is
lower than the desired selling price. Buyers who wish to
purchase the property are encouraged to build on the
property offering a higher amount than the current im-
plementation of the auction. The auction ends when no
one wants to raise the bet and the property is granted to
the best buyer.

APN Model for Specification of the Communication Protocols in Multi-Agent System 17
Figure 4. AUML representation of protocol FIPA contract
net [13].
Figure 5. FIPa English auction protocol [13].
4. Modeling Interaction Protocols
4.1. Engineering Protocols in MAS
Several studies in the literature [2,6,15,16] were inter-
ested in the proposal of an interaction protocol engineer-
ing that will guide the designer from specification to
validation. Some of those researches have correspon-
dence with the communication protocols in distributed
systems as [2,15]. Others researchers have developed a
process for development of interaction protocol specific
to multi-agent systems. In this context, [17] proposed
protocol engineering in five steps:
 Analysis,
 A formal description,
 Validation,
 Implementation,
 Testing.
4.2. Properties of an Interaction Protocol in a
MAS
When looking the model of protocol for dialogue agents,
there are two essential aspects which are: specification
and flexibility [17].
Flexibility: It is very important to design a flexible
protocol insofar as it is possible to achieve the desired
goal without affecting the autonomy of agents [4]. Ac-
cording to [18], it is interesting to consider interaction
protocols of small a designed as micro-protocols, and
combine them to form more complexes and more spe-
cific task. This is particularly useful since most com-
monly found similar dialogue structures in different in-
teraction protocols. Allowing the composition of mi-
cro-protocols then promotes reuse [19] and contributes to
the specification of flexible protocols and its extension
become easier.
Specification: It is important to use a formalism that
allows specifying interaction protocols with a high level
of abstraction. According to [18], a protocol must be in-
dependent of the domain and architecture of agents who
will use it. [18] Indicates that it is also impor tant to ad opt
a declarative approach to explicitly state the rules of
protocols. In fact, the formalism should allow specifying
interaction protocols as clearly as possible while having a
good power of expression. In addition, a protocol must
be specified as to allow possible to verify properties such
as deadlock, termination, etc.
5. Modeling Interaction by MAS
5.1. Assumptions and Framework
Before detailing the model we specify the assumptions
and framework:
 MAS that we consider consist of a set of cognitive
agents, running in parallel.
 Agents communicate by sending synchronous mes-
sages (the sender is blocked until the recipient has
received the message or until a response is received
possibly with a maximum waiting period).
 To understand and be able to communicate perfectly,
we also assume that:
 The agents share a common ontolog y.
 They are equipped with memory (each agent keeps
track every time it performs an event).
 They are intelligent (each agent has a strategy of
resolution and a reasoning mechanism) to retain and
use the content and history of their conversations.

APN Model for Specification of the Communication Protocols in Multi-Agent System
18
5.2. APN Model for Interaction Protocol
Precisely, the underlying idea of Agent Petri Nets is that
they can properly represent the agent and its autono my in
communication with other agents in its environment or
other environments, while maintaining a fairly simple
and understandab le graphical representation. APN mode l
transitions correspond to actions that can be performed,
places are the variables of the states containing tokens
corresponding to agents and arcs, according to their ori-
entation, determines the activation conditions of a tran-
sition and its effect on the state.
Formalism is considered reliable if it ensures some
important properties such as synchronization, compete-
tion but also reusability. It is therefore natural to com-
pose models of complex protocols from simple protocols
or a set of protocol elements by connecting their bows
and places synchronization.
This is why we try to give our early model open con-
nection between two agents A1 and A2, the protocol is
said elementary and aims to establish a connection be-
tween two agents and can be reused in other models. In-
deed, A1 sends a connection request (call) to A2 by
sending request message (F (A1, A2)). After receipt of
the request, A2 can accept the call by sending a message
(m’) to agree or to refuse. So we can define m as (m’ =
{agree, refuse}).
The protocol ends with the receipt of the agreement
From A2. A2 is connecting to new environment. So, A1
and A2 cross their transition (Success: T7). If A2 refuses
the request of A1 then A1 receiving a message refuses
(Failed: T8) as shown in Figure 6.
In the case of connection failure due to a refusal on th e
part of A2, we can consider checkpoints in our model
APN. Indeed, A2 sends <A2.refuse> message and can
A2
A1
A2:
P1
P2
P3
P5
P4
P7
P6
T1 T2
T3
T4 T5
T6
T7
A1:request
A2.refus e
A2.Agree
A1:
Engagement
environne ment
<A1>
<A1,A2>
<A2>
<A2>
A1.req(F(A1,A2)) <A1.m> <A1.m>
<A2>
<A2> <A2>
<A2>
<A1>
<A1>
<A2.m'>
<A1>
<A2.refus e>
<A2.Agree>
m:request(F(A1,A2))
m'={agree, refuse}
<A1>
Echec
<A2>
Attent e
<A1>
P8
T8
receive
response
Succes
receive
request
Figure 6. Open_connection APN model.
return to its original state. A1, after receiving this mes-
sage, returns to its original state and another instance of
the protocol can be triggered.
We opt to FIPA standards that are more used to pre-
sent the interaction between agents process. In the re-
mainder of this session, we modeling two simple proto-
cols defined in FIPA which are “Inform” and “Request”.
We present a variant of “FIPA-Contract Net” protocol
involving more than two agents.
FIPA-Inform: It is a simple communicative act to pass
information from one agent to another. There are two
agents interact: A1 sends a message inform (T1) to A2.
A2 receives this message and processes (T2). The con-
versation ends when both agents cross their transitions
(T3) and (T4) as shown in the figur e be low :
It was assumed in the protocol that the two agents are
already in communication (connection opening). Basicly,
we using basic “Open_connection APN model”. It is a
reusability method .
A1 send the message “inform” using the function Ft
(A1, A2) = <1, A1.inform, 0>, indicate that the two
agents in communication are A1 and A2. A1 is the
transmitter, the receiver is A2 and the message sent by
A1 is “inform”. Receiving the message is validated by
the value 1 in the third field of the Ft1 function (A1, A2)
upon receipt.
With Ft () function we can model sending message to
inform several agents always keeping the same syntax:
Figure 7. APN model of FIPA-Inform protocol.

APN Model for Specification of the Communication Protocols in Multi-Agent System 19
the recipients are in brackets and the transmitter is A1,
for example, inform A2, A3 and A4 is presented by: Ft
(A1, A2, A3, A4) = <1, A1.inform, 0>.
FIPA-Request: The idea is to present a communication
protocol between two agents A1 and A2. An agent A1
sends a request to another agent A2 to perform an action
P. The receiver may grant or refuse to perform the action
as described in Figure 8. In case of refusal, the receiving
agent is obliged to disclose the reason for the rejection.
This is one of the FIPA-Request protocols as shown in
the diagram below.
Figure 9 describe the same protocol using Petri Nets.
Each agent executes a Petri net whose places correspond
to its state or the condition of the conversation and tran-
sitions correspond to sending and receiving messages.
Interpretation: Despite the simplicity of protocol, sev-
eral places, transitions and arcs were used to model the
state of the conversation and agents throughout their
communication.
In the conventional model, the designer has to model
two cases each time. For example, B want execute P and
the inverse case. The numbers of places used tokens are
not distinguished and are increase.
So, the goal is to create a valid model for the two
agents in which the location of the officer’s decision
must be explicit, this is possible with the use of tokens as
agents identified by their Names.
We try to model this same protocol by APN and we
refine our model by integrating primitives of ACL lan-
guage.
A1 sends a connectio n request to A2 with the primitive
request. A2 may accept the application, it responds him
in this case with a message <A2. agree>, and <A2. re-
fuse> if he refuses demand. In case of non un d erstan ding,
A2 sends <A2.not-under stood>.
In the case of acceptance of A2, it tries to Run P: send
a message <A2.inform-done>. In the case of failure the
message sended is <A2. failure>. However, this failure
Request
Refused( reasons)
Not-understood Agree
Fa ilure( re a s o n s)Inform-done
Figure 8. FIPA-Request
leaves the possibility to redo the task A2. To do this con-
trol, we must add checkpoints in our model.
The Petri net of Figure 10 model the protocol stated
above that describes the statements relating to the inte
action between the two ag ents. We distinguish three pos-
Figure 9. Petri nets model for FIPA-Request protocol [20].
A2
Agree
Failure
Request Request
Refuse
Agree
Refuse
Restart Inform-done
A1
<A1> <A2>
Réception de
demande
Agree
Refused
Not-understood <A2>
<A1>
<A1>
<A2>
A2 e ssai
e
de faire P
Réception de
réponse
Succès
Echec
Figure 10. APN model for FIPA-Request.

APN Model for Specification of the Communication Protocols in Multi-Agent System
20
sible situations: success, failure due to rejection of the
application and failu re in achieving the task.
Formally, the model specifies how the interaction be-
tween these two agents occurs and what performative are
used at each step of the conversation.
The following figure illustrates the APN model for
FIPA-Request protocol detailed with messages exchanged
between agents and the functions used.
Note that in this model, it is always possible to capture
the current state of the conversation or the agent through
current location of tokens (agents).
Interpretation: In this model it was supposed that the
two agents are engaged in the same environment of com-
munication. First, the connection is created by Open_con-
nection APN model betw een A1 and A2.
In addition, we detailed our APN model FIPA-Request
specifying the different exchanged between the two
agents. We propose the structure of each message in our
model with the function Ft (Ai, Aj): Ai is the transmitter
and A2 is the receiver.
In both cases of failure, a new instance of the protocol
can be triggered and checkpoints or host states can be
Figure 11. Detailed APN model for FIPA-Request.
added. Indeed, A2 must specify the reasons for refusal.
This refusal can be either because it does not have the
skills to do the job or because he does not want this job.
In this second case A1 can throw a new conversation.
The first case is due to the refusal of A2: the two
agents will cross the end transition T6 and can return to
the initial state by adding an arc from T6 to P1.The sec-
ond case of failure is due to a problem in the realization:
A2 may decide to repeat the task, then add a arcc from
T9 to P8.
Note that the agents in question are cognitive agents
having the ability to make decisions and act autonomously
while following the rules of protocol. An agent can get
stuck in a state of waiting for an answer.
However, in order to more improve our models based
on APN, you can insert a timing mechanism that uses a
delay () function and a maximum R beyond which the
agent leaves the wait state. This solution allows us to
avoid an agent stuck wait a long time.
FIPA-Contract Net
In the following section, we will try to show the power of
formalism APN in modeling protocols involving multiple
agents such as FIPA-Contract Net Protocol. In this pro-
tocol, a moderator agent chooses an agent that he does
not know his skills to perform a task by broadcasting a
request message to perform a task P.
Our goal is not modeli ng t he l ocal behavi or of t he agent ,
for it was assigned to the moderator agent to choose the
first positive response and refu se all that come after. This
agent can cancel the negotiation during the conversation
as shown in Figure 12.
There are several possible scenarios:
 All agents do not accept the offer of the moderator:
failure.
 There is a positive response. In this case, three cases
are possible.
 If the moderator accepts the offer (acceptproposal):
success.
 If the moderator cancels negotiation (cancel): failure.
 the moderator refused all offers except the first po-
sitive (reject-propo sal).
6. Conclusions
In this paper, we proposed a model for specifying com-
munication protocols in MAS based on APN. Our goal
was to model the interactions among agents by provid-
ing a formal model for many FIPA Protocols.
It is undeniable that the use of interaction protocols for
conversations greatly facilitates the development of sys-
tems based on communicating agents. We believe that
the limitations inherent in other formalisms described
necessitate the use of a formalism supporting competition
and factorization for modeling such complex and com-
peting interactions.

APN Model for Specification of the Communication Protocols in Multi-Agent System 21
Figure 12. APN model for FIPA-Contract net protocol.
The major contribution of APN model is the power
expressing based on agents. This formal method can ver-
ify correctly the interaction between them by specifying
the messages exchanged during the conversation and
during interaction.
Some issues remain open for future developments,
such as parameterization of protocols. For example, dur-
ing an auction, how long an agent is permitted to wait
before performing task? Otherwise, we can extend our
model by incorporating a timeout mechanism and excep-
tion handling to avoid blocking during conversations.
REFERENCES
[1] G. Chicoisne, “Dialogue between Natural Agents and
Artificial Agents: An Application to Virtual Communi-
ties”, Ph.D. Thesis, National Institute of Polytechnique of
Grenoble, 2004.
[2] H. Mazouzi, “Engineering of Interaction Protocols: Dis-
tributed Multi-Agent Systems to Systems”, Ph.D. Thesis,
University of Paris IX-Dauphine, 2001.
[3] B. Marzougui, K. Hassine and K. Barkaoui, “A New For-
malism for Modeling a Multi Agent Systems: Agent Petri
Nets”, Journal of Software Engineering and Applications
(JSEA), Vol. 3, No. 12, 2010, pp. 1118-1124.
doi:10.4236/jsea.2010.312130
[4] B. Marzougui, K. Hassine and K. Barkaoui, “Method for
Verification of a Multi Agents System”, 2011 Second In-
ternational Conference on Intelligent Systems, Modelling
and Simulation (ISMS), Phnom Penh, 25-27 January 2011,
pp. 62-65.
[5] B. Marzougui, K. Hassine and K. Barkaoui, “Modeling
Migration of Mobile Agents,” Business Process Man-
agement Workshops, Vol. 132, 2012, pp. 530-540.
[6] Y. Charif and N. Sabouret, “Interaction Protocol for Ser-
vice Composition in the Room,” JFSMA’06, Annecy,
2006, pp. 253-266,
[7] J. L. Koning and I. V. Hernández, “Generating Machine
Processable Representations of Textual Representations
of AUML,” Third International Workshop, AOSE’02,
Bologna, Vol. 2585, 2003.
[8] M. Augeraud, F. Colléand and D. Sarramia, “Design Cen-
ter Interaction: Application to the Design of Interactive
Simulation,” International Conference on INFORSID’06,
Hammamet, 2006.
[9] J. L. Koning and S. Pesty, “Communication Patterns in
Principles and Architectures of Multi-Agent Systems,”
Hermes Science Publications, Paris, 2001.
[10] M.Koji, S. Jin-Hua and O. Yasuhiro, “Study on Common
Coordinate System by using Relative Position of Other
Autonomous Robot,” SICE Annual Conference, Akita,
20-23 August 2012.
[11] I. R. Hernandez, “Modelling, Formal Specification and
Verification of Interaction Protocols: A Role-Based Ap-
proach,” Ph. D. Thesis, National Institute of Polytech-
nique of Grenoble, 2004.
[12] A. Pauchet, “Cognitive Modelling of Human Interactions
in a Collaborative Planning Framework,” Ph.D. Thesis,
University of Paris IX-Dauphine, 2004.
[13] Foundation for Intelligent Physical Agents (FIPA), “Speci-
fication: Agent Communication Lang uage,” 2001.
http://www.fipa.org
[14] S. Singh, M. Kearns and M. Littman, “Graphical Models
for Game Theory,” Proceedings of the 17th Conference in
Uncertainty in Artificial Intelligence, Seattle, 2-5 August
2001, pp. 253-260.
[15] A. El Fallah Seghrouchni, “Coordination of Agents: Mod-
els and Algorithms Protocols,” HDR Research, Univer-
sity of Paris, 2000.
[16] C. Sibertin-Blanc, “A Layered Model for the Engineering
of Interaction Protocols,” Formalizing Competing Activi-
ties, FAC’02, Toulouse, 2002.
[17] B. Chaib-draa, I. Jarras and B. Moulin, “Multi-Agent Sys-
tems: General Principles and Applications,” In J. P. Briot
and Y. Demazeau, Eds., Agent and Multi Agents System,

APN Model for Specification of the Communication Protocols in Multi-Agent System
22
Hermes, Ottawa, 2001.
[18] H. D. Burkhard, “Liveness and Fairness Properties in
Multi-Agent Systems,” International Joint Conference on
Artificial Intelligence IJCAI’93, Chambery, 28 August-3
September 1993, pp. 325-330.
[19] M. Greaves, H. Holmback and J. Bradshaw, “What Is a
Conversation Policy,” Proceeding Issues in Agent Com-
munication, 2000, pp. 118-131.
[20] R. G. Smith, “The Contract Net Protocol: High-Level
Communication and Control in a Distributed Problem
Solver,” IEEE Transactions on Computers, Vol. C-29, No.
12, 1980, pp.1104-1113. doi:10.1109/TC.1980.1675516