Carolina Howard Felicíssimo*, Carlos José Pereira de Lucena* and Jean-Pierre Briot**
* DI/PUC-Rio, Rua Marquês de São Vicente 225, 22453-900, RJ, Brazil
** LIPVI/ParisVI, Avenue du Président Kennedy, 75016, Paris, France
Keywords: Normative Open Multiagent Systems, Electronic Agent-Based Organizations/Institutions.
Abstract: A major challenge in the research of multiagent systems (MAS) is the design and implementation of open
MAS in which norms can be effectively applied to their agents and easily managed. These tasks are arduous
because norms are usually written for general purposes, hindering a more precise regulation. The motivation
for this research came forth from the need to resolve this challenge, providing an approach applicable in
open systems. In such systems, heterogeneity and autonomy rule out any assumption concerning the way
third-party entities are implemented and behaved. This paper summarizes the result of a study done on solu-
tions for the modeling of MAS. That study motivates the development of our DynaCROM approach.
Three main observations summarize the starting
point of this research. Firstly, “autonomous agents
and MAS represent a new way of analyzing,
designing and implementing complex software
systems” (Jennings, 1998). Those systems are
usually formed by rich social interactions, i.e., by
agents cooperating, coordinating and/or negotiating
(Jennings, 2001).
Secondly, with the Web evolving towards a Se-
mantic Web (Berners-Lee et al., 2001), it is believed
that available information will be presented in a
meaningful way for allowing not only humans to
process its content, but also (software) agents. In this
scenario, agents will be able to migrate among MAS
in order to obtain resources and/or services not
found in their original systems. Thus, if one main
contribution of Semantic Web can be singled out, it
has to be openness. Openness will permit new types
of applications for MAS, as ubiquitous systems
(Weiser, 1991), in which dynamicity, due to inter-
nal/external events, is a key characteristic.
Thirdly, considering that MAS will be open in
nature, norms play a central role in the social phe-
nomena occurring in the MAS field, which is mov-
ing more and more from the individual, cognitive
focused agent models to models of socially situated
agents. In normative MAS (NMAS), the main posed
question is: “How to ensure efficiency at the level of
MAS whilst respecting individual autonomy?” (Boel-
la, 2006). NMAS as an area of research has become
a major issue in the MAS field and it can be situated
at the intersection of normative systems and MAS.
Following these three main observations, it is be-
lieved that upcoming information systems will be
implemented as open MAS formed by several goal-
oriented problem-solving entities.
Openness has consequences for the design, im-
plementation and use of information, requiring novel
modeling primitives and methods in order to make a
MAS a real application. Solutions for open MAS
must deal with issues inherent to open environments,
namely: heterogeneity of agents; trust and accounta-
bility; exception handling (detection, prevention and
recovery from failures that may jeopardize the glob-
al operation of the system); and, societal change
(capability of accommodating structural changes)
(Dignum et al., 2007; Al-Muhtadi et al., 2003).
A very dynamic, open and distributed domain –
like the Semantic Web and applications for ubiquit-
ous computing, both that can be implemented by
MAS – is always subject to unanticipated events
(Hewitt, 1991), caused by malicious agents that do
not conform to recommendations of correct and
incorrect behaviors. This risk imposes the necessity
for regulatory mechanisms for preventing undesira-
ble actions to happen and, consequently, to inspire
trust for the members of the system.
This paper presents a study that focuses on solu-
tions for the modeling of MAS. The study means to
be an overview of the existing works on multiagent
organisations and normative multiagent systems.
The result of that study motivates the development
of our DynaCROM approach (meaning Dyna
Felicíssimo C., Lucena C. and Briot J. (2009).
In Proceedings of the International Conference on Agents and Artificial Intelligence, pages 540-546
DOI: 10.5220/0001663705400546
ontextual Regulation Information Provision in
Open MAS). From the individual agents’ perspec-
tive, DynaCROM is an information mechanism that
makes application agents aware of the norms they
are bound to at a given moment. From the system
developers’ perspective, DynaCROM is a methodol-
ogy that operationalizes regulative norms in open
MAS, enabling developers to embody abstract
norms with domain values.
Further details about specific aspects of Dyna-
CROM can be found in more specialized publica-
tions. In (Felicíssimo et al., 2008b), the guidelines to
operationalize regulative norms in NMAS by using
DynaCROM are presented. Following those guide-
lines, concrete norms are reached from abstract ones,
operationalized in a NMAS. In (Felicíssimo et al.,
2008a), the details about how DynaCROM contex-
tualizes norms in a NMAS, from the perspectives of
individual agents and the system developer, are
provided. In (Felicíssimo et al., 2008c), a case study
from the television domain and, in (Felicíssimo et
al., 2007), a case study from the domain of multina-
tional corporations are presented.
The remainder of this paper is organized as fol-
lows. Section 2 gives an overview of the foundations
upon the modeling of MAS. Basic theories and re-
lated research fields are analyzed in order to provide
readers with a better understanding about the con-
cepts and ideas described in this paper. Section 3
discusses current solutions for MAS. Section 4 fina-
lizes the paper by presenting our conclusions.
Traditional modeling of MAS often assumes an
individualistic perspective in the sense that agents
are considered autonomous entities, pursuing their
own individual goals based on their own beliefs and
capabilities. Even in this perspective, global behav-
iour emerges from individual interactions and, there-
fore, the modeling has to be expanded to consider
not only an agent-centric view, but also societal and
organizational-centric views. Furthermore, the
overall problem of analyzing the social, legal, eco-
nomic and technological dimensions of an agent
organization is not normally considered when, ide-
ally, it should be resolved.
Agent-centered approaches can be useful for
closed systems, composed of a small number of
agents, but they fail to design open systems
(Rodríguez-Aguliar, 2001; Esteva et al., 2003). For
instance, in critical applications such as those within
business, environments or government agencies
(hospitals, police, justice, etc.), the structural charac-
teristics of the domain have to be incorporated. That
is, the design of an agent society must also consider
organizational characteristics such as stability over
time, some level of predictability, commitment to
aims and strategies, and so on.
The idea of modeling MAS as organizations was
early proposed by (Gasser et al., 1987; Pattison et
al., 1987; Corkill and Lesser, 1983; Werner, 1987)
and it is still a major issue in the MAS research
field, especially in applications on the areas of Ser-
vice Oriented Computing, Grid Computing and
Ambient Intelligence. Recently, the subject of MAS
design from the organizational perspective has been
mainly discussed in the COIN workshop (COIN,
URL), which has been held yearly since 2005, as a
dual event co-located within large international
conferences of the area in different geographic re-
Even with this research effort, organizational ap-
proaches have not been a common use in MAS,
which is usually seen as a pure aggregation of
agents. The fact that organizational approaches have
not been effectively adopted suggests that some
work still needs to be done in providing better tools
for the design and implementation of MAS in which
intrinsic characteristics of the application domain
(e.g., society structure) can be considered. Moreo-
ver, this necessity increases when considering open
systems from particular ‘cultures’ (i.e., “the predo-
minating attitudes and behavior that characterize
the functioning of a group or organization” (EDic-
tionary, URL)).
In the next subsections, two major research lines
for the modeling of MAS will be presented and,
then, discussed. The first research line proposes the
modeling of MAS based on organizations. The
second one proposes the modeling of MAS based on
the electronic institutional aspects of organizations.
By ‘electronic institutional’ aspects, the authors
mean an organization restricted through the defini-
tions of all the following: related roles, common
language, valid interactions and set of norms.
2.1 Electronic Agent-Based
The definition of the organization term usually va-
ries between two meanings for MAS researchers. In
the first meaning, an organization is often unders-
tood as an entity with identity that represents (not
identical) groups of agents. In the second meaning,
an organization is often understood as constraints
(structures, norms and patterns) found in a social
context that shapes the actions and interactions of
agents (Coutinho et al., 2005).
The first sense of an organization comes from an
administrative/economic point of view: organiza-
tions are like enterprises that perform some service
or produce some goods. The second sense comes
from a sociological point of view: an organization is
better called the social organization implicitly or
explicitly present in a society, community or groups
of agents that shape the interactions among agents.
These two meanings of an organization are not
mutually exclusive; the second meaning is more
general than the first one. Thus, it is natural to say
that every organization (first meaning) has a social
organization (second meaning), but the opposite is
not always true – every social organization (second
meaning) does not always give rise to an organiza-
tion (first meaning).
Considering the case that every organization has
a social organization, the latter is materialized in the
first one by the specification of the structure and
objectives of the system. Thus, a social organization
is envisioned by the organization as a whole and by
describing the activity of the system as realized by
the individual agents (Vázquez-Salceda et al., 2005).
In this sense, the organizational dimension covers
both the organization and the agent perspectives in
the design of agent societies.
The work on MAS modeling based on the orga-
nizational dimension mainly started with the emer-
gence of the HarmonIA (Vázquez-Salceda and Dig-
num, 2003) and OperA (Dignum, 2004) formal
frameworks. HarmonIA provides the way to model
especially highly regulated electronic organizations
from the abstract level, where norms are usually
defined, to the final protocols and procedures that
implement those norms. The HarmonIA framework
also incorporates ontologies to describe and connect
different levels of norms.
OperA is a formal specification framework that
focuses on the organizational dimension, properly
modeling not only organizational structures in an
agent society (that structures the global behavior of
the society), but also the aims and behavior of the
agents from the agent perspective. The framework
also explicitly provides a solution for ontological
descriptions of agent interactions.
In (Vázquez-Salceda et al., 2005), the O
tional Model for Normative Institutions (OMNI)
framework is presented, resulting from the combina-
tion of some aspects of the HarmonIA and OperA
frameworks. The OMNI framework focuses on the
organization dimension (that also structures the
global behavior of the society), on the behavior of
the agents from the agent perspective, on agent inte-
ractions and on a normative structure that is separate
from the agents that will populate the MAS.
In order to support the development of closed-
systems and open, flexible environments, OMNI
presents a rigid specification of its structure, defin-
ing particular fields for the description of scenes,
roles and groups of roles. There are no normative
aspects further than the ones for organizations, roles,
group of roles, agent interactions and agents (only
norms for roles, group of roles, scene and transition
can be specified). The organization entity is not
explicitly present. An organization is formed by
listing all its institutional roles (e.g., managers, di-
rectors, president, etc.) and represented when agents
play those roles. Currently, OMNI does not provide
a solution for the implementation and integration of
its specifications in a given MAS.
Another important line of research, based on or-
ganizational models for MAS, is mainly proposed by
Sichman, Boissier and their colleagues with their
work started with
OSE (Hannoun et al., 2000).
OSE is an organizational model for MAS based on
three major concepts: the roles which constrain the
individual behaviors of agents, the organizational
links that regulate social exchanges between agents
and the groups which constrain the layout of agents
involved in strong interactions.
In (Hübner et al., 2002), the work on
evolved resulting in the
permits the specification of a MAS organization
along the structural and functional dimensions,
which can be specified independently of one anoth-
er. Furthermore,
makes explicit the deontic
relation which exists between both dimensions. In
short, the
organizational model enables the
declaration of the MAS organizational structure
(roles, groups and links), functioning (a set of global
goals and plans), obligations and permissions.
2.2 Electronic Agent-based Institutions
The idea of modeling MAS as institutions came
from the observation that human institutions (North,
1990) have been successfully mediating human
interactions for centuries and, so, EI (meaning E
tronic Institution(s)) may cope with a similar re-
sponsibility within agent societies. The aim of the
proposal is to promote a natural extension of human
institutions by permitting not only humans, but also
autonomous agents to interact with one another in a
reliable way. This way, EI can be seen as the elec-
tronic counterpart of a human institution in which
interactions between agents are articulated through a
role-based multiagent protocol specification.
ICAART 2009 - International Conference on Agents and Artificial Intelligence
The work on formalization of EI has been done
for years and it is extensively presented mainly in
(Noriega, 1997), (Rodríguez-Aguilar, 2001) and
(Esteva, 2003). In (Noriega, 1997), the different
components of an institution are introduced by using
a typical trading institution – the fish market auction
houses – as a motivating example. Noriega proposes
that an institution is defined by: (i) a set of roles and
relationships within them, (ii) a common ontology
and communication language which allow heteroge-
neous agents to exchange knowledge, (iii) the valid
interactions that agents may have structured in con-
versations, and (iv) a set of rules of behavior which
determine the actions that agents must take under
certain circumstances.
In (Rodríguez-Aguilar, 2001), the formalization
of EI presented by Noriega was extended and re-
fined, resulting in the definition of ways of realizing
EI. Rodríguez-Aguilar proposes an infrastructure to
implement EI that can be realized by making use of
a special type of mediator agents, the so called inte-
ragents (Martín et al., 2000). Each agent involved
in a conversation is connected to an interagent,
which mediates the agent’s interactions in one-to-
one conversations.
In (Esteva, 2003), the previous work done by
(Noriega, 1997; and, Rodríguez-Aguilar, 2001) on
the formalization of EI was continued. In his work,
Esteva provides support for the specifications of EI,
their automatic verification and also their realization.
His main concrete result, the ISLANDER graphical
editor, was developed as a generic infrastructure
which could be used for the deployment and verifi-
cation of the specified institutions.
The limitation of the Rodríguez-Aguilar’s work
in which only one-to-one conversations could be
mediated by interagents was improved in Esteva’s
work. There, for each conversation, a governor agent
(an evolution of the interagent one) has two queues,
one for the messages received from its associated
agent and another one for the messages received
from the social layer agents. As a case study, Esteva
evolved the previous examples of Noriega and
Rodríguez-Aguilar on fish markets, now regarding
multi-market institutions instead of only single-
market ones.
Many other publications of EI have appeared re-
cently (e.g., Esteva et al., 2004; García-Camino et
al., 2005 and 2006; Grossi et al., 2007), expanding
the work on the subject.
In (Esteva et al., 2004), the AMELI agent-based
middleware is proposed as an infrastructure that
mediates agents’ interactions while enforcing institu-
tional norms. The combination of ISLANDER and
AMELI supports the design and development of
open MAS adopting a social perspective.
In (García-Camino et al., 2005), a distributed ar-
chitecture for EI is proposed in order to endow MAS
with a social layer in which normative positions are
explicitly represented and managed via rules for
regulation. In (García-Camino et al., 2006), the rule-
based language from the authors is better detailed as
a declarative normative language that can represent
distinct flavors of deontic notions and relationships.
Every external agent from the architecture has a
dedicated governor agent linked to it that enforces
the norms of executed events.
In (Grossi et al., 2007), the work on formaliza-
tion of EI is continued, focusing on both institution
and its components (abstract and concrete norms,
empowerment of agents and roles). Yet, a formal
relation between institutions and organizational
structures is also defined in such a way that institu-
tional norms can be refined to construct – organiza-
tional structures – which are closer to an imple-
mented system. Thus, the gap between abstract
norms and concrete system specifications is better
Despite all work done, a MAS implemented as
an EI is still understood as a type of dialogical sys-
tem that simply structures agent interactions by
establishing the commitments, obligations and rights
of participating agents. However, the solution not
only structures interactions, but also enforces indi-
vidual and social behaviours by obliging every agent
to act according to the defined norms.
We agree that the following current limitations
of EI can also be outlined: (i) there are no normative
aspects further than the ones for roles, agent interac-
tions and agents; (ii) the specification of an EI is
often too society-centric
in the sense that it com-
pletely fixes agent interactions in rigid protocols and
interfaces; (iii) external agents have no room for
autonomous behavior, i.e., they blindly follow de-
fined protocols with the only autonomy to accept or
reject them; (iv) all possible interactions among
agents have to be defined; (v) it is difficult, if not
impossible, to describe indirect interactions; this is
due to the fact that all interacting activity taking
place in an EI is purely dialogic by means of direct
communication between the agents; and, (vi) the
structure of an EI is static and, so, cannot evolve at
system runtime.
The models used to describe or design an organiza-
tion are classically divided into the agent-centered
or organizational-centered perspectives (Lemaître
and Excelente, 1998). In the first perspective, system
developers try to analyze and/or design a whole
MAS that shows a non-accidental and non-chaotic
global behavior starting from the agents (parts of the
In the open MAS scenario, the basic problem
with the agent-centered idea is that the system de-
veloper has no control anymore over the creation of
the agents. Thus, at any time, external heterogeneous
agents can join or leave an open MAS and, then,
disrupt the existing order. As long as open MAS are
highly desirable to face today’s increasingly distri-
buted and interconnected computing demands, this
wish poses problems that still need concrete solu-
In the last few years, one promising path of re-
search and development has been an organizational-
centered analysis and design of MAS (second pers-
pective). In this attempt, system developers proceed
in a top-down fashion, explicitly defining both the
organization entity (external to the agent level) and
the organization statutes that agents must comply
with. The statutes of an organization indicate, at the
most abstract level, the main objectives of the organ-
ization and the values that direct the fulfilling of its
objectives. Moreover, statutes also point to the con-
text in which the organization will have to perform
its activities (Vázquez-Salceda et al., 2005).
Analyzing several organizational-centered mod-
els found in the literature (e.g., OMNI (Vázquez-
Salceda et al., 2005), ISLANDER (Esteva et al.,
(Hübner et al., 2002)), we agree
with (Coutinho et al., 2008a) about the two main
sources of difficulties found on organizational-
centered models.
The first source of difficult is that the very notion
of organization admits and is frequently used with
slightly different interpretations. Sometimes, the
organization term refers to “collectivities oriented to
the pursuit of relatively specific goals and exhibiting
relatively highly formalized social structures
(Scott, 1998). Other times, the term refers to stable
social patterns/structures of joint activity that con-
strains and drives the actions and interactions of
agents towards a purpose.
The second source of difficulty is that the organ-
ization entity can be described in several modeling
dimensions (e.g., in the structural and functional
These two sources of difficulties of organiza-
tional-centered models are important and should be
considered because each proposal of an organiza-
tional model makes a particular ontological com-
mitment in regard to them.
A proposal for an integrated ontology, which is
developed in a bottom-up manner from the existing
organizational models, is presented in (Coutinho et
al., 2008). The main purpose of such ontology is the
creation of an interoperation mechanism that can be
used by heterogeneous organizational models for
handling interoperability among open organization-
al-centered MAS. However, the proposal is an ongo-
ing work and, therefore, needs to be concluded.
In (Vázquez-Salceda et al., 2005), some draw-
backs of current approaches for MAS modeling also
are pointed out, as follows.
MAS modeling are too agent-centric or too or-
ganizational-centric. Some methodologies (e.g.,
GAIA (Wooldridge, 2000); Prometheus (Winikoff
and Padgham, 2004)) are too agent-centric, in the
sense that they are mainly focused on the model of
single agents, and give limited support to model the
dynamic interactions of the agents in the agent so-
ciety. Other methodologies (e.g., SODA (Omicini,
2001) and ISLANDER) are too society-centric in the
sense that they completely fix agent interactions in
rigid protocols and interfaces. Thus, agents cannot
exercise their characteristic of autonomy.
Roles and agents are usually treated without an
explicit distinction. This distinction is an important
asset in order to establish a difference between orga-
nizational values and individual (agent) values.
Normative aspects are not often considered or,
when considered, they are either too theoretical (i.e.,
the conceptual model of the solution does not have
an implemented solution for it) or too practical (i.e.,
the implemented solution does not have a conceptual
model to guide its specifications). Furthermore, few
agent methodologies cover normative aspects and
they usually do it by trying to model the whole nor-
mative environment in only one level of abstraction,
either too theoretical (by means of computationally
hard logics) or too practical (by means of the usage
of policies or protocols).
Ontologies are often seen as an external (acces-
sory) component, while in fact they should be tightly
coupled with the rest of the system when used to
model most of its elements.
Three main assumptions underlie this research.
Firstly, MAS has emerged as a concrete solution to
develop complex software systems in which mono-
lithic architectures (based on objects) have been
replaced by distributed ones (based on agents). Se-
condly, with the advent of the Semantic Web, agents
will be able to process information from different
ICAART 2009 - International Conference on Agents and Artificial Intelligence
sources and, so, they will be able to move around
other MAS looking for resources and/or services not
found locally. In this scenario, openness will be an
intrinsic and mandatory characteristic of upcoming
systems. However, openness without control leads to
chaotic scenarios. The use of norms in MAS is a
promising approach for achieving openness in a
reliable way. So, the final assumption of this work is
that MAS should be normative.
However, despite all efforts made to move theory
and practice of MAS from closed to open agent
societies, current solutions do not yet explicitly
support openness and its consequences. More pre-
cisely, methodologies, modeling languages and tools
(e.g., frameworks, platforms), needed for imple-
menting open MAS, do not conveniently cover the
aspects of regulation and domain representation for
society differentiation.
This paper presents an overview of the existing
works on multiagent organisations and normative
multiagent systems. The study done on solutions for
the modeling of MAS has led to the development of
our DynaCROM methodology. We agree that the
DynaCROM methodology supports the system de-
veloper in his task of implementation and manage-
ment of regulative norms in MAS.
To our Pronex-Faperj project (E-26/170.011/2008).
Al-Muhtadi, J.; et al., 2003. Cerberus: a context-aware
security scheme for smart spaces. In 1
IEEE Interna-
tional Conference On Pervasive Computing And
Communications (PerCom 2003). p. 489- 496.
Berners-Lee, T.; et al, 2001. The Semantic Web, Scientific
American. 284(5), p. 34–43, May 2001.
Boella, G.; et al, 2006. Introduction to normative multia-
gent systems. Journal of Comput. Math. Organ.
Theory. v. 12, Issue 2–3, ISSN 1381-298X, p. 71–79.
COIN, URL: <>.
Coutinho, L. dos R.; et al, 2005. Modeling organization in
MAS: a comparison of models. In 1
Workshop on
Software Engineering for Agent-Oriented Systems.
Coutinho, L. dos R.; et al., 2008. Modeling Dimensions
for Multi-Agent Systems Organizations. In Multi-
Agent Systems: Semantics and Dynamics of Organiza-
tional Models book, IGI global.
Corkill, D.D. and Lesser, V. 1983. The use of meta-level
control for coordination in a distributed problem solv-
ing network. In 8
International Joint Conference on
Artificial Intelligence, p. 748–756.
Dignum, V., 2004. A Model for Organizational Interac-
tion: based on Agents, founded in Logic. PhD Thesis.
Dignum, F.; et al., 2007. Open Agent Systems. In 8
International Workshop on AOSE, USA.
EDictionary, URL: <>
Esteva, M.; et al, 2002. ISLANDER: an electronic institu-
tions editor. International Conference on Autonomous
Agents and Multiagent Systems, p. 1045–1052.
Esteva, M., 2003. Electronic Institutions: from specifica-
tion to development. PhD thesis, Technical University
of Catalonia.
Esteva, M.; et al. 2004. AMELI: An Agent-based Mid-
dleware for Electronic Institutions. In 3
Joint Conference on Autonomous Agents and Multia-
gent Systems, p. 236–243.
Felicíssimo, C.; et al. 2007. Informing Regulatory Dynam-
ics in Open MAS. In LNCS, v. 4386. p. 147–162.
Felicíssimo, C. H.; et al, 2008a. Contextualizing Norma-
tive Open Multi-Agent Systems. In 23
Annual ACM
Symposium on Applied Computing (ACM SAC).
Felicíssimo, C.; et al., 2008b. DynaCROM: An Approach
to Implement Regulative Norms in Normative Multi-
agent Systems. In 3
DEON’08 International Work-
shop on Normative Multiagent Systems (NorMAS).
Felicíssimo, C.; et al. 2008c. How to Concretize Norms in
NMAS? An Operational Normative Approach Pre-
sented with a Case Study from the Television Domain.
In: COIN at AAAI’08.
García-Camino, A.; et al. 2005. A Distributed Architecture
for Norm-Aware Agent Societies. In Declarative
Agent Languages and Technologies (DALT’05).
García-Camino, A.; et al., 2006. Norm-Oriented Pro-
gramming of Electronic Institutions: A Rule-based
Approach. In: COIN@AAMAS2006, Japan.
Grossi, D.; et al. 2007. A Formal Road from Institutional
Norms to Organizational Structures. In AAMAS'07.
Hannoun, M.; et al., 2000. MOISE: An organizational mo-
del for multi-agent systems. LNAI, v.1952, p.152–161.
Henricksen, K. and Indulska, J. 2005. Developing context-
aware pervasive computing applications: models and
approach. Pervasive and Mobile Computing.
Hewitt, C. Open Information Systems Semantics for Dis-
tributed Artificial Intelli-gence. Artificial Intelligence,
v.47, I.1-3, 1991, p. 79–106, ISSN: 0004-3702.
Hübner, J. F.; et al. 2002. A model for the structural,
functional, and deontic specification of organizations
in multiagent systems. LNAI, v. 2507. p. 118–128.
Jennings, N.; et al., 1998. A Roadmap of Agent Research
and Development. In JAAMAS, v. 1, p. 7–38.
Jennings, N. R., 2001. An agent-based approach for build-
ing complex software systems. Communications of the
ACM, 44(4), p. 35–41.
Gasser, L.; et al., 1987. Distributed Artificial Intelligence,
chapter MACE: A flexible testbed for distributed AI
research, p. 119–152, Pitman Publishers.
Lemaître C. and Excelente, C. B., 1998. Multi-agent or-
ganization approach. In 2
Iberoamerican Workshop
on DAI and MAS.
Martín, F. J.; et al. 2000. An infrastructure for agent-based
systems: An interagent approach. International Journal
of Intelligent Systems, 15(3), p. 217–240.
Noriega, P., 1997. Agent-Mediated Auctions: The Fish-
market Metaphor. PhD thesis, Technical University of
North, D. 1990. Institutions, Institutional change and
Economics Performance. Cambridge, U.P..
Omicini, A., 2001. Soda: Societies and infrastructures in
the analysis and design of agent-based systems. In:
LNAI, v. 1957, p. 185–193.
Pattison, H.E.; et al., 1987. Distributed Artificial Intelli-
gence, chapter Instantiating Descriptions of Organiza-
tional Structure, p. 59–96, Pitman Publishers.
Rodríguez-Aguilar, J.A., 2001 On the Design and Con-
struction of Agent-mediated Electronic Institutions,
PhD thesis, Universitat Autonoma de Barcelona.
Scott, W. R., 1998. Organizations: rational, natural and
open systems. Upper Saddle River, NJ: Prentice Hall.
Vázquez-Salceda, J. and Dignum, F., 2003. Modelling
electronic organizations. In LNAI, v.2691, p.584–593.
Vázquez-Salceda, J.; et al, 2005.. Organizing Multiagent
Systems. In JAAMAS, 11(3), 2005, p. 307–360.
Weiser, M., 1991. The computer for the twenty-first cen-
tury. Scientific American, 265(3), p. 94–104.
Werner, E., 1987. Distributed Artificial Intelligence. In:
Chapter Cooperating Agents: A Unified Theory of
Communication and Social Structure, p. 3–36.
Winikoff, M. and Padgham, L., 2004. Developing Intelli-
gent Agent Systems: A Practical Guide. Book. Pub-
lished by John Wiley and Sons. ISBN 0-470-86120-7.
Wooldridge, M.; et al., 2000. The Gaia Methodology for
Agent-Oriented Analysis and Design. In: AAMAS,
3(3), p.285–312.
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