OMNI: Introducing Social Structure, Norms and
Ontologies into Agent Organizations
Virginia Dignum, Javier Vázquez-Salceda, and Frank Dignum
Institute of Information and Computing Sciences,
Utrecht University, The Netherlands
{virginia, javier, dignum}@cs.uu.nl
Abstract. In this paper, we propose a framework for modelling agent
organizations, Omni, that allows the balance of global organizational requirements
with the autonomy of individual agents. It specifies global
goals of the system independently from those of the specific agents that
populate the system. Both the norms that regulate interaction between
agents, as well as the contextual meaning of those interactions are important
aspects when specifying the organizational structure. Omni integrates
all this aspects in one framework. In order to make design of the
multi-agent system manageable, we distinguish three levels of abstraction
with increasing implementation detail. All dimensions of Omni have
a formal logical semantics, which ensures consistency and possibility of
verification of the different aspects of the system. Omni is therefore utmost
suitable for the modelling of all types of MAS from open to closed
environments.
1 Introduction
In closed domains, the design of MAS can suffice with the idea that agents
are mere performers of organizational roles or functions, interacting according
to fixed protocols and unable to deviate from expected behavior [21]. As such,
agent autonomy is rather limited. In open domains, agents are self-governed
autonomous entities that pursue their own individual goals based only on their
own beliefs and capabilities [1].
Comprehensive models for MAS must, on the one hand, be able to specify
global goals and requirements of organizations but, on the other hand, cannot assume
that participating agents will act according to the needs and expectations
of the system design. Concepts as organizational rules [20], norms and institutions
[6], [7], and social structures [13] arise from the idea that the effective
engineering of MAS needs high-level, agent-independent concepts and abstractions
that explicitly define the organization in which agents live [21]. These are
the rules and global objectives that govern the activity of an enterprise, group,
organization or nation.
Given that agents might deviate from expected behavior, open societies need
mechanisms to systematize, defend and recommend right and wrong behavior,
R.H. Bordini et al. (Eds.): PROMAS 2004, LNAI 3346, pp. 183–200, 2005.
c○ Springer-Verlag Berlin Heidelberg 2005
184 V. Dignum, J. Vázquez-Salceda, and F. Dignum
which can inspire trust into the agents that will join them. Norms are commonly
used means to describe such expected behavior. Finally, organizational models
must provide means to represent concepts and relationships in the domain that
are rich enough to cover the necessary contexts of agent interaction while keeping
in mind the relevance of those concepts for the global aims of the system.
In this paper we propose a framework for agent organizations, Omni(Organizational
Model for Normative Institutions) presenting a first attempt to cover
all the above mentioned aspects in a way that is usable for both open and closed
systems.
The paper is organized as follows: In §2 we present a generic description of
the Omni framework. In §3, we discuss the abstract level of an organization.
Then we will focus on the description of the Organizational dimension (§4), the
Normative dimension (§5) of the e-Organization and present an outline in §6 of
the kind of ontologies and communication languages needed in the Ontological
Dimension. In §7 we compare our framework with other well known models.
We end this document with our conclusions and outline future lines of research.
Throughout the paper the different components of a society are illustrated using
an organization that has as main global objective the realization of conferences.
2 The Omni Framework
Omni is an integrated framework for modelling a whole range of MAS, from
closed systems with fixed participants and interaction protocols, to open, flexible
systems that allow and adapt to the participation of heterogeneous agents with
different agendas. This approach is rather unique, as most existing frameworks
concentrate in a specific type of MAS. Omni is composed by three dimensions:
Normative, Organizational and Ontological that describe different characterizations
of the environment. The model is based on two recent MAS models,
OperA [5], and HarmonIA [18]. Figure 1 depicts the different modules that
compose our proposed framework organized into three levels of abstraction:
– the Abstract Level: where the statutes of the organization to be modelled
are defined in a high level of abstraction. This step is similar to a first step
in the requirement analysis. It also contains the definition of terms that are
generic for any organization (that is, that are incontextual) and the ontology
of the model itself.
– the Concrete Level: where all the analysis and design process is carried
on, starting from the abstract values defined in the previous level, refining
their meaning in terms of norms and rules, roles, landmarks and concrete
ontological concepts.
– the Implementation Level: where the design in the Normative and Organizational
dimensions is implemented in a given multi-agent architecture,
including the mechanisms for role enactment and for norm enforcement.
The division of the system into these three levels aims to ease the transition
from the very abstract statutes, norms and regulations to the very concrete
OMNI: Introducing Social Structure, Norms and Ontologies 185
Fig. 1. The Omni framework
protocols and procedures implemented in the system. Different domains have
different requirements concerning normative, organizational and communicative
characteristics, which means that not always all three modules have the same
impact or are even needed: in those domains with none or small normative
components, design is mainly guided by the Organizational Dimension, while in
highly regulated domains the Normative Dimension is the most prominent.
3 The Abstract Level
Statutes indicate, at the most abstract level, the main objective of the organization,
the values that direct the fulfilling of this objective and they also point to
the context where the organization will have to perform its activities.
In the conference scenario, we can take as example a research consortium
such as the IFMAS (International Foundation for Multi-Agent Systems). The
statutes state: ”IFMAS is a non-profit corporation whose purpose is to promote
science and technology. In pursuit of its purposes, IFMAS will engage in activities
including, but not limited to: (1) Coordinating and arranging seminars on
artificial intelligence and multi-agent systems; (2)...”. In this statement we can
find:
1. the objectives: the main objective of this organization is to promote science
and technology. Another objective is the organization of seminars.
2. the context: IFMAS states that it operates in the area of artificial intelligence
and multi-agent systems.
3. the values: The IFMAS is a non-profit organization. Implicit in the latter
part, it also says that sharing is also a value of the organization.
The objectives of the organization express the overall goals of the society. As
far as the organization has control over the actions of the agents acting within
that organization, it will try to ensure that they perform actions leading to the
186 V. Dignum, J. Vázquez-Salceda, and F. Dignum
overall goal of the society. We will see in §4.1 and §4.2 how these objectives
influence the design process in the Organizational Dimension.
The values of the organization are beliefs that individuals have about what
is important, both to them and to the society as a whole. A value, therefore,
is a belief (right or wrong) about the way something should be. Values define
beliefs about, for instance, what is acceptable or unacceptable, good or bad. In
our framework, values are the basis of the Normative Dimension.
The environment, or context, of an organization can be seen as consisting
essentially of other societies or organizations that are interdependent and each
influence the other.
4 The Organizational Dimension
The design of agent organizations must capture on the one hand, the structure
and requirements of the society owners, and on the other hand, must assume that
participating agents must be available that are able and interested in enacting
society roles. In Omni, the Organizational Dimension consists of a 3-layered
model: based on the concerns identified in the Abstract Level, the Concrete
Level specifies the structure and objectives of a system as envisioned by the
organization, and the Implementation Level describes the activity of the system
as realized by the individual agents. This separation enables Omni models
to respect the autonomy of individual agents while ensuring conformance to
organizational aims.
4.1 The Organizational Abstract Level
The abstract level of the Organizational Dimension describes which are the aims
and concerns of the organization with respect to the social system. At the abstract
level, as we saw in §3, this is defined by means of a list of the organization’s
externally observable objectives, that is, the desired states of affairs in the life
of the society. These abstract objectives are translated into the specific objectives
of the society model. In the case of our example, the abstract objective
of ”coordinating and arranging seminars...” is translated into the objective of
organizing a specific conference.
A common way to express the objectives of an organization is in terms of
its expected functionality. The determination of the overall objectives of the
society follows a process of elicitation of functional (what) and interaction (how)
requirements. For example, how should a conference be organized, in terms of
program, location, co-located workshops, etc. To identify the objectives of an
organization, it is important to characterize the different stakeholders (who) of
the organization, their requirements, expectations, constraints and relationships
to each other. Stakeholders in the conference scenario are researchers, organizers,
etc. Stake holders are the basis for the identification of roles in the concrete level
of specification of an organization (see §4.2).
OMNI: Introducing Social Structure, Norms and Ontologies 187
4.2 The Organizational Concrete Level
The Concrete Level of the organizational dimension specifies the means to achieve
the objectives identified in the the abstract level as an Organizational Model
(OM). The OM describes the structure and global characteristics of a domain
from an organizational perspective. That is, from the premise that it is the
society goals that determine roles and interaction norms. Organizational characteristics
of an agent society are specified in the OM in terms of its Social (§4.2)
and Interaction Structures (§4.2).
The definition of these structures alone is not enough, as specification of a
society should include the description of concepts and relations holding in the
domain, and of those behaviours accepted as ’good’. Therefore, these structures
should be linked with the role norms, scene norms and transition norms, defined
in the concrete level of the Normative Dimension (see §5.2), and with the
ontologies and communication languages defined in the concrete level of the
Ontological Dimension (see §6).
The organization design is also guided by the coordination needs of the domain.
These determine the type of roles and tasks necessary to facilitate the
tasks of the organization. We identify three basic coordination types: market,
hierarchy and network that are defined as Architectural Templates.
The Social Structure. The social structure of an organization describes the
roles holding in the organization. It consists of a list of role definitions, Roles
(including their objectives, rights and requirements), such as PC-member, program
chair, author, etc.; a list of role groups’ definitions, Groups; the relations
between roles by a Role Hierarchy graph, and a Role Dependencies graph.
Roles are the main element of the Social Structure. From the society perspective,
role descriptions should identify the activities and services necessary
to achieve society objectives and enable to abstract from the individuals that
will eventually perform the role. From the agent perspective, roles specify the
expectations of the society with respect to the agent’s activity in the society. In
Omni, the definition of a role consists of an identifier, a set of role objectives,
possibly sets of sub-objectives per objective, a set of role rights, a set of norms
and the type of role. An example of role description is presented in table 1. The
meaning and relationships between the concepts used is formally specified in the
Ontological Dimension, and the formal specification of norms in the Normative
Dimension.
Groups provide means to collectively refer to a set of roles. Moreover, groups
are used to specify norms that hold for all roles in the group. Groups are defined
by means of an identifier, a non-empty set of roles, and the group norms. Norms
of a group must be consistent with the norms of the roles in the group. An
example of a group in the conference scenario is the organizing team consisting
of the roles program chair, local organizer, and general chair.
Abstract society objectives form the basis for the definition of the objectives
of roles. The distribution of objectives in roles is defined by means of the Role
Hierarchy. Different criteria can guide the definition of Role Hierarchy. In par-
188 V. Dignum, J. Vázquez-Salceda, and F. Dignum
Id PC member
Table 1. PC member role description
Objectives paper reviewed(Paper,Report)
Sub-objectives {read(P), report written(P, Rep), review received(Org, P, Rep)}
Rights access-confmanager-program(me)
Norms & PC member is OBLIGED to understand English
Rules IF paper assigned THEN PC member is OBLIGED
Type external
to review paper BEFORE given deadline
IF author of paper assigned is colleague
THEN PC member is OBLIGED to refuse to review ASAP
Fig. 2. Role dependencies in a conference
ticular, a role can be refined by decomposing it in sub-roles that, together, fulfill
the objectives of the given role. This refinement of roles defines Role Dependencies.
A dependency graph represents the dependency relations between roles.
Nodes in the graph are roles in the society. Arcs are labelled with the objectives
of the parent role for whose realization the parent role depends on the child role.
Part of the dependency graph for the conference society is displayed in figure 2.
For example, the arc between nodes PC-Chair and PC-member represents the
dependency PC-Chair �paper−reviewed PC-member. The way the objective g in
a dependency relation r1 �g r2 is actually passed between r1 and r2 depends
on the coordination type of the society, defined in the Architectural Templates.
In Omni, we identify three types of role dependencies: bidding, request and delegation.
OMNI: Introducing Social Structure, Norms and Ontologies 189
Fig. 3. Landmarks pattern for review process
The Interaction Structure. Interaction is structured in a set of meaningful
scenes that follow pre-defined abstract scene scripts. Examples of scenes are the
registration of participants in a conference, which involves a representative of
the organization and a potential participant, or paper review, involving program
committee members and the PC chair. A scene script describes an scene by its
players (roles), its desired results and the norms regulating the interaction. In
the OM, scene scripts are specified according to the requirements of the society.
The results of an interaction scene are achieved by the joint activity of the
participating roles, through the realization of (sub-)objectives of those roles. A
scene script establishes also the desired interaction patterns between roles, that
is, a desired combination of the (sub-) objectives of the roles.
Table 2. Script for the Review Process scene
Scene Review Process
Roles Program-Chair (1), PC-member(2..Max)
Results r1 = ∀ P ∈ Papers: reviews done(P, review1, review2)
Interaction Patterns PATTERN(r1): see figure 3
Norms & Rules Program-Chair is PERMITTED to assign papers
PC-member is PERMITTED to review papers assigned
before deadline
In Omni, interaction description is declarative in nature, rather than describing
the exact activities. Interaction objectives can be more or less restrictive,
giving the agent enacting the role more or less freedom to decide how to achieve
the role objectives and interpret its norms. Following the ideas of [15], we call
such expressions landmarks, that is, conjunctions of logical expressions that are
true in a state. Figure 3 shows the informal landmark pattern for the Review
Process.
Several different specific actions can bring about the same state, that is, landmarks
actually represent families of protocols. The use of landmarks to describe
activity enables the actors to choose the best applicable actions, according to
their own goals and capabilities.
The relation between scenes is represented by the Interaction Structure (see
figure 4). In this diagram, transitions describe a partial ordering of the scenes,
190 V. Dignum, J. Vázquez-Salceda, and F. Dignum
Fig. 4. Interaction Structure in the Conference scenario
plus eventual synchronization constraints. Note that several scenes can be happening
at the same time and one agent can participate in different scenes simultaneously.
Transitions also describe the conditions for the creation of a new
instance of the scene, and specify the maximum number of scene instances that
are allowed simultaneously. Furthermore, the enactment of a role in a scene may
have consequences in following scenes. In these cases the evolution relations between
roles describe the constraints that hold for the role-enacting agents as
they move from scene to scene.
4.3 The Organizational Implementation Level
Omni assumes that individual agents are designed independently from the society
to model goals and capabilities of a given entity. Individual agents will join
a society as enactors of organizational role(s), as a means to realize their own
goals [3].
Social Model. Agent populations of the organizational model are described
in the social model (SM) in terms of commitments regulating the enactment of
roles by individual agents. Depending of the specific agents that will join the
organization, several populations are possible for each organizational model.
When an agent applies, and is accepted, for a role, it will commit itself to the
realization of the role goals and to act within the society according to the role
constraints. The commitments are specified as social contracts. A social contract
describes the conditions and rules applying to an agent enacting role(s) in the
agent society. Given an agent society S, a social contract for agent s enacting
role r is defined as a tuple
social-contract = 〈a, r, CC〉
where a is an agent, r ∈ roles(S) is a role, and CC is a set of contract clauses
(including (1) the time period the contract holds -either from date to date,
or until certain states hold; (2) specific agreements and conditions governing
the role enactment, and (3) the sanctions to take when norms are violated).
In the conference scenario, when a researcher becomes PC member, her social
OMNI: Introducing Social Structure, Norms and Ontologies 191
contract will describe for example the agreements concerning number of papers
to review (which possibly may deviate from the standard number desired by the
conference).
Social contracts identify role enacting agents (reas) that compose the society.
For each agent, the rea reflects the agent’s own requirements and conditions concerning
its participation in the society. Making agreements explicit and formal,
allows the verification of whether the animated society behaves according to the
design specified in the OM. Social contracts in Omni are a two-sided agreement
between agents and roles instead of a one-sided API description of role enactment,
as have been proposed by other researchers [16, 12]. In the extreme, if all is
expressed in the role definition and no room is left for negotiation, Omni social
contracts can function as these API’s.
Interaction Model. Omni provides two levels of specification for interactions.
While the OM provides a script for interaction scenes according to the organizational
aims and requirements, the IM, realized in the form of contracts, provides
the interaction scenes such as agreed upon by the agents. Due to the autonomous
behavior of agents, the interaction model must be able to accommodate other
interaction contracts describing new, emergent, interaction paths, to the extent
allowed by the organizational and social models.
An interaction scene results from the instantiation of a scene script, described
in the OM, to the reas actually enacting it and might include specializations or
restrictions of the script to the requirements of the reas. An interaction contract
describes the conditions and rules applying to interaction between agents in the
agent society. That is, the clauses in an interaction contract specify actual instantiations
of interaction scene scripts and must indicate the actors involved
and the specific agreements and sanctions concerning the scene to be played.
The contract must furthermore involve sufficient reas to cover all the needed
roles in the scene. Besides the refinement of the script to the desires and characteristics
of the agents participating in the scene instance, interaction contracts
must describe the protocol agreed by those agents to fulfil the script landmarks.
Interaction protocols are the concrete representation of the refinement of scene
script landmarks with the particularities imposed by the participants to the specific
communicative capabilities of those participants. Given a society S and a
scene s ∈ scenes(S), an interaction contract is defined as a tuple
interaction-contract = 〈A, s, CC, P 〉
where the set of agents A = {a ∈ Agents : rea(a, r, s)|r ∈ roles(s)} represents
the set of all agents enacting reas participating in interaction scene s, CC is
a set of contract clauses, that is, possible conditions and deadlines concerning
the results and interaction patterns of scene s, and P is the protocol to be followed.
Protocols describe the actual interaction between reas. A rea interaction
protocol describes a communication pattern for reas that fulfills the scene script
landmarks. In the conference scenario, an interaction contract for the Review
Process scene can specify, for example, that actors will follow the ConfMaster
protocol.
192 V. Dignum, J. Vázquez-Salceda, and F. Dignum
5 The Normative Dimension
In the same way as the Organizational Dimension, the Normative Dimension is
composed by the different levels of abstraction. The translation steps from one
level to the following are described in a formal way, as we aim to to be able
to verify if a given organization complies to all the norms that are specified in
the regulations. The connection between levels is very useful not only in its topdown
direction (guiding the design), but also from bottom up (agents can trace
the origin of a given protocol and reason in terms of the rules and norms the
protocol implements).
5.1 The Normative Abstract Level
The values and objectives of an organization described in the Abstract Level, can
be described as the desires of the society model. For example, for the Conference
Society :
– the information sharing value can be described as D(share(info)),
– the non-profit value can be described as D(non-profit(organization)),
However, besides a formal syntax, this does not provide any meaning to the
concept of value. That is, values do not specify how, when or in which conditions
individuals should behave appropriately in any given social setup. This will be
defined later by abstract norms, concrete norms and rules (see section 5.2). In
Omnithe meaning of the values is defined by the norms that contribute to this
value. In an intuitive way we can see this translation process as follows:
⊢org D(ϕ) ↦→ Oorg(ϕ)
meaning that, if an organization org values situations where ϕ holds higher than
situation where ϕ does not hold, then such value can be translated in terms of
a norm (an obligation of the organization org) to fulfill ϕ. In our framework a
norm contributes to a value if fulfilling the norm always leads to states in which
the value is more fully accomplished. So, each value has attached a list of norms
that contribute to that value.
⊢IFMAS D(share(info)) ↦→ OIFMAS(disseminate(research))
We define ANorms (the language for abstract norms) to be a deontic logic
that is temporal, relativized (in terms of roles and groups) and conditional, i.e.,
an obligation to perform an action or reach a state can be conditional on some
state of affairs to hold, it is also meant for a certain type (or role) of agents and
should be fulfilled before a certain point in time. For instance, the following norm
might hold: “The authors should submit their contributions before the deadline”,
which can be formalized as:
Oauthor(submit(paper) < Deadline)
The obligation is directed towards the author, assuming that she is responsible
for fulfilling it.
OMNI: Introducing Social Structure, Norms and Ontologies 193
5.2 The Normative Concrete Level
In order to check norms and act on possible violations of the norms by the agents
within an organization, the abstract norms have to be translated into actions and
concepts that can be handled within such organization. To do so, the definition
of the abstract norms are iteratively concretized into more concrete norms, and
then translated into the rules, violations and sanctions that implement them.
The Norm Level. The norms at this level are described in CNorms (the
language for concrete norms), which we assume for the moment to be equal
to ANorms, but which might use different predicates. In addition we define a
function I: ANorms → CNorms which is a mapping from the abstract norms
to the concrete ones. For each abstract norm I indicates how it can be fulfilled by
fulfilling concrete norms within the context of this organization. This function
is based on the counts-as operator as developed in [8].
There are several ways in which norms can be abstract and thus several
ways to make them more concrete [18]. As an illustration of this process, in the
following we describe two kinds of abstractness.
Abstract actions: Actions that can be implemented in many ways. For example:
“submitting a paper”. The translation in this case is a kind of definition of
the abstract action in terms of concrete ones:
send mail(organizer, files) ∪ send post(organizer, hard copies)
⇛IFMAS submit(paper)
Temporal abstractness: Often there is an implicit deadline for obligations.
E.g., the obligation of reviewing the paper occurs only if the paper is assigned,
and if so the review should be done before the deadline:
done(assign paper(P,me,Deadline)) →
OPC member(review paper(P, Rep) < do(pass(Deadline)))
The Rule Level. The translation from norms to rules in Omni marks a transition
from a normative perspective to a more descriptive one. Such translation
also implies a change in the language, from deontic logic to a Propositional Dynamic
Logic (a language more suitable to express actions and time constraints).
Each norm can be translated into:
a) a violation expression: by using the following reduction rule by Meyer [10]:
O(α) ↦→ [¬α] V
b) a precedence expression: in those cases where the norm expresses temporal
relations among actions, such relation can be also expressed through the [ ]
operator as follows:
O(α <do(β)) ↦→ [β] done(α)
O(α <do(β)) ↦→ ¬done(α) → [β] V
194 V. Dignum, J. Vázquez-Salceda, and F. Dignum
The first reduction rule translates the temporal constraint of α being done before
β with an expression in Dynamic Logic that states: ”once action β is performed,
it should always be the case that action α has been done”. The second reduction
rule expresses the violation condition: ”if action α has not been done, once action
β is performed it always is the case that violation V occurs”.
Id PC member
Table 3. Formal specification of PC member role
Objectives paper reviewed(Paper,Report)
Sub-objectives {read(P), reported(P, Rep), review received(Org, P, Rep)}
Rights access-confman-program(me)
Norms OPC member(understand(English))
done(assign paper(P,me,Deadline)) →
OPC member(review paper(P, Rep) < do(pass(Deadline)))
done(assign paper(P,me, )) ∧ is a direct colleague(author(P)) →
OPC member(review refused(P) < pass(TOMORROW))
Rules done(assign paper(P,me,Deadline)) ∧¬done(review paper(P, Rep))
Type external
→ [pass(Deadline)] V4
done(assign paper(P,me, )) ∧ is a direct colleague(author(P)) ∧
¬done(review refused(P)) → [pass(TOMORROW)] V5
By means of this refinement process, the designer can obtain all the norms
and rules that apply in the system, and then include them in the organizational
model. An example of the formalization of the role norms introduced in table 1
is given in table 3.
In Omni, violations are the key concept in norm enforcement. We separate
the violations coming from the behavior of external entities (external violations)
from the ones related to the behavior of the internal agents (internal violations)
Internal violations describe states that the organization should always avoid.
As the designer has full control of the design of the organization’s own agents,
such internal agents will fully comply with the organizational objectives and
follow its norms and rules. In this case the aim is not to create an enforcement
mechanism but a continuous safety control of the system’s behavior (i.e., avoid
the system to enter in a non-desirable, illegal state because of a failure in one of
the agents).
In our framework, external violations are the ones where the designer should
pay more attention. As we cannot assume that agents entering into the organization
will always follow the norms and rules imposed by its normative system,
an active enforcement should be made by the internal agents. In our framework,
internal agents do not have access to the internal beliefs, goals and intentions of
the other agents, they can only check the agents’ behavior, by detecting when
those agents enter in states considered illegal. The way of doing so is by means
of the list of definitions of external violations. Such list defines, for each violation,
the condition that triggers it. This condition is extracted from the rule that
OMNI: Introducing Social Structure, Norms and Ontologies 195
defines the violation. As an example, let us take one of the rules identified for
the PC member role in table 3:
done(assign paper(P,me,Deadline))
∧¬done(review paper(P,Rep)) → [pass(Deadline)] V4
we can create the condition for violation V 4 by stating that the action inside
[ ] has been done while the other preconditions are true. Then we should also
add the sanction (the actions carried against the violator), the side-effects (the
actions to be done to counter-act the violation) and the enforcing roles (the role
or roles that have the responsibility to detect this type of violations):
Violation: IFMAS:V4
Pre-conditions: done(assign paper(P,me,Deadline))
∧¬done(review paper(P, Rep)) ∧ done(pass(Deadline))
Sanction: delete from PC list(me))
Side-effects: { find new reviewer(P,r2); assign paper(P,r2,Deadline2) }
Enforcing roles: { organizer, session chair}
5.3 The Normative Implementation Level
There are two main approaches to implement the rules in the rule level: a) creating
a rule interpreter that any agent entering the organization will incorporate,
and b) translating the rules into protocols to be included in the interaction contracts
Note that in both cases it is not ensured that the agents will follow those
descriptions. The violations in the rule level should also be translated in some
detection mechanisms to check the behavior of the agents.
At Implementation Level, the organization model provides both the low-level
protocols and the related rules. Agents that are only able to follow protocols will
blindly follow them, while the ones that can also interpret the rules (Deliberative
Normative Agents [4]) can choose between following the protocol or reasoning
about the rules, or do both. With this approach the autonomy of the agents
entering the organization is adapted to their reasoning capabilities, which makes
Omni utmost adequate to model open environments. Norm Autonomous Agents
that are able to reason about norms, can switch from following low-level protocols
to higher level rules and norms, by using the links provided by Omni from
procedures to rules, and from rules to norms. An example is shown in figure 5.
6 The Ontological Dimension
The main challenge of coordination and collaboration in open environments is
that of mutual understanding. Communication mechanisms include both the representation
of domain knowledge (what are we talking about) and protocols for
communication (how are we talking). Both content and protocol have different
meanings at the different levels of abstraction (e.g. while at the abstract level
196 V. Dignum, J. Vázquez-Salceda, and F. Dignum
Fig. 5. An example of the refinement process
one might talk of disseminate, such action will most probably not be available to
agents acting at the implementation level). Specification of communication content
is usually realized using ontologies, which are shared conceptualizations of
the terms and predicates in a domain. Agent communication languages (ACLs)
are the usual means in MAS to describe communicative actions. ACLs are wrapper
languages in the sense that they abstract from the content of communication.
In Omni, the Ontological Dimension describes both the content and the language
for communication, at three different levels of abstraction. At the Abstract
Level, the Model Ontology can be seen as a meta-ontology that defines all the
concepts of the framework itself, such as norms, rules, roles, groups, violations,
sanctions and landmarks.
The content aspects of communication, or domain knowledge, are specified
by Domain Ontologies. InOmni abstract concepts can be iteratively defined
and refined in terms of more concrete concepts. The Concrete Domain Ontology
includes all the predicates and elements that appear during the design of the
Organizational and Normative Structure, and the Procedural Domain Ontology,
with the terms from the domain that will be finally used in the implemented
system. Concepts or predicates at a lower abstraction level, count as, or implement,
concepts at the higher levels. For instance, the actual realization of the
AAMAS’04 conference counts-as the IFMAS’s objective organize-conference defined
in the Organizational Model, which in turn counts-as the IFMAS’s value
of disseminate knowledge, described in its statutes.
Communication Acts define the language for communication, including the
performatives and the protocols. At the Concrete Level, Generic Communication
Acts define the interactions languages used in the Organizational Model, while
OMNI: Introducing Social Structure, Norms and Ontologies 197
the Specific Communication Acts covers the communication languages actually
used by the agents as they agree in the interaction contracts. As with the content
ontologies, communicative acts defined at a lower level of abstraction implement
those defined at a higher level.
7 Discussion: Omni Compared with Other Approaches
Development methods for multi-agent systems are currently a hot research topic
and several approaches have been proposed. Comprehensive methodologies to design
agent societies must be able to describe the characteristics of organizational
environments. Such environments are best understood in terms of social concepts
such as organization structures, norms and domain language. Furthermore,
methodologies must support the development of open societies and the specification
of formal institutions. These are issues covered by the Omni framework.
In the remainder of this section, we briefly discuss how some well known models
support the social and normative concepts introduced by the Omni framework.
GAIA. Gaia [19] is one of the first agent-oriented software engineering methodologies
that explicitly takes into account social concepts. Gaia models are situated
in at the Concrete Level of Omni (cf. figure 1). While the Implementation
Level is explicitly and purposefully ignored, Gaia does not have any notion of an
Abstract Level. Gaia is only concerned with the society level and does not capture
internal aspects of agent design. However, societies are only considered from
the perspective of the individual participants, and therefore Gaia does not deal
with communication or other collective issues. Furthermore, normative aspects
are reduced to static permissions, a sort of constraints or rules and behavior is
fixed in protocols. Moreover, Gaia is not suited to model open domains, and
cannot easily deal with self-interested agents, as it does not distinguish between
organizational and individual aspects, and does not provide capabilities for agent
interpretation of society objectives, norms or plans.
SODA. SODA [11], is actually an extension to Gaia that enables open societies
to be designed around suitably-designed coordination media, and social rules to
be designed and enforced in terms of coordination rules. As Gaia, SODA distinguishes
between an analysis and a design phase. As an attempt to include an
higher abstraction level (cf. figure 1), SODA presents a notion of the context,
or environment, of the society, albeit not explicit. However, even though SODA
distinguishes between agent and collective spaces, it sees roles as the representation
of the observable behavior of agents, and therefore cannot represent the
difference between the organizational perspective on the activity and aims of
individuals (represented by the concept of role in Omni ) from the agent perspective
on its own activity and aims (represented by the concept of agent in
Omni and linked to the role by a social contract). Role enactment is fixed in
SODA as the agent model that maps roles to agent classes without any possibility
to accommodate agent preferences or characteristics (agent classes are
198 V. Dignum, J. Vázquez-Salceda, and F. Dignum
pure specifications of the role characteristics). There are no normative aspects
in SODA further than the notion of permission to access infrastructure services.
Communication primitives are limited to interaction protocols, and SODA provides
no explicit representation for the domain ontology. Furthermore, SODA
also does not have a clear and formal semantics.
ISLANDER. The ISLANDER formalism [7] provides a formal framework for
institutions [14] and has proven to be well-suited to model practical applications
(e.g. electronic auction houses). This formalism views an agent-based institution
as a dialogical system where all the interactions inside the institution are
a composition of multiple dialogic activities (message exchanges). Furthermore,
the e-INSTITUTOR platform and the ISLANDER API enable the animation
of models and the participation of external agents. The activity of these agents
is, however, constrained by governors that regulate agent actions, to the precise
enactment of the roles specified in the institution model. In contrary to the
other frameworks discussed here, ISLANDER provides a sound model for the
domain ontology and has a formal semantics [14]. However, ISLANDER provides
no primitives to model the Abstract Level of an organization and does not
consider the normative aspects of organizations, further than the specification
of constraints for scene transition and enactment (the only allowed interactions
are those explicitly represented by arcs in scenes).
TROPOS. TROPOS methodology [2] spans the overall development process.
It distinguishes between an early and a late requirements phase, and between architectural
design and detailed design. The models are implemented using Jack
Intelligent Agents [9], which is an agent-oriented extension of Java. Tropos is a
fairly complete methodology that considers all steps in system development, and
it treats both inter-agent and intra-agent perspectives. The early requirement
phase of Tropos, can be seen as a specification of the Abstract Level proposed by
Omni (cf. figure 1). The late requirements phase comes fairly close to the idea
of Concrete Level in Omni , except that it does not provide explicit concepts
to capture norms, and ontological aspects are only implicitly described. At the
Implementation Level, Tropos provides a detailed implementation of organizational
models into JACK agents. The main two shortcomings of Tropos are that
a) it is not formal (although there is some ongoing work on providing a formal
semantics for Tropos), and b) it is too organizational-centered in the sense that
is does not consider that agents can have their own goals and plans, and not
just those coming from the organization. Furthermore, Tropos has no concept
representing the normative aspects of an organization.
Conclusions
In this paper we introduced Omni, a modelling framework for different types of
MAS, from closed systems to open, flexible environments. This approach is rather
unique, as most existing frameworks concentrate on a specific type of MAS.
OMNI: Introducing Social Structure, Norms and Ontologies 199
The modular structure of Omni facilitates the adaptation of the framework
to different types of domains. In those domains with none or small normative
components, design is guided by the Organizational Dimension, while in highly
regulated domains the Normative Dimension is more prominent and therefore
guides the design.
All dimensions of Omni have a formal logical semantics, which ensures consistency
and possibility of verification of the different aspects of the system. For
more information on the formalization aspects, we refer the reader to [5] for a
detailed specification of the formalization of the organizational and ontological
dimensions, and to [17] for the formal normative model.
Currently we are taking the first steps towards implementing tools to use
with the framework. We will be using ISLANDER as a basis for the support of
the implementation level and build the other levels on top of that.
References
1. G. Abdelkader. Requirements for achieving software agents autonomy and defining
their responsibility. In Proc. Autonomy Workshop at AAMAS 2003.
2. P. Bresciani, P. Giorgini, F. Giunchiglia, J. Mylopoulos, and A. Perini. TROPOS:
An agent-oriented software development methodology. Journal of Autonomous
Agents and Multi-Agent Systems, to appear.
3. M. Dastani, V. Dignum, and F. Dignum. Role assignment in open agent societies.
In Proc. AAMAS’03, 2003.
4. F. Dignum. Autonomous Agents with Norms. AI and Law, 7:69–79, 1999.
5. V. Dignum. A Model for Organizational Interaction: based on Agents, founded in
Logic. SIKS Dissertation Series 2004-1. SIKS, 2004. PhD Thesis.
6. V. Dignum and F. Dignum. Modeling agent societies: Coordination frameworks and
institutions. In P. Brazdil and A. Jorge, editors, Progress in Artificial Intelligence,
LNAI 2258, pages 191–204. Springer-Verlag, 2001.
7. M. Esteva, J. Padget, and C. Sierra. Formalizing a language for institutions and
norms. In J.-J.CH. Meyer and M. Tambe, editors, Intelligent Agents VIII, volume
2333 of LNAI, pages 348–366. Springer Verlag, 2001.
8. D. Grossi and F. Dignum. Abstract and concrete norms in institutions. Accepted
in FAABS 2004, 2004.
9. Nick Howden, Ralph Rnnquist, Andrew Hodgson, and Andrew Lucas. Jack - summary
of an agent infrastructure. In 5th International Conference on Autonomous
Agents. 2001.
10. J.-J. Ch. Meyer. A different approach to deontic logic: Deontic logic viewed as a
variant of dynamic logic. Notre Dame J. of Formal Logic, 29(1):109–136, 1988.
11. A. Omicini. Soda: Societies and infrastructures in the analysis and design of agentbased
systems. In P. Ciancarini and M. Wooldridge, editors, Agent-Oriented Software
Engineering, volume 1957 of LNAI, pages 185–193. Springer Verlag, 2001.
12. A. Omicini. Towards a notion of agent coordination context. In D. Marinescu and
C. Lee, editors, Process Coordination and Ubiquitous Computing, pages 187–200.
CRC-Press, 2002.
13. H.V.D. Parunak and J. Odell. Representing social structures in uml. In
M.Wooldridge, G.Weiss, and P. Ciancarini, editors, Agent-Oriented Software Engineering
II, LNCS 2222. Springer-Verlag, 2002.
200 V. Dignum, J. Vázquez-Salceda, and F. Dignum
14. J.A. Rodriguez. On the Design and Construction of Agent-mediated Electronic
Institutions. PhD thesis, Institut d’Investigació en Intel.ligència Artificial (IIIA),
2001.
15. I. Smith, P. Cohen, J. Bradshaw, M. Greaves, and H. Holmback. Designing conversation
policies using joint intention theory. In Proc. ICMAS-98, pages 269–276.
IEEE Press, 1998.
16. W. Vasconcelos, J. Sabater, C. Sierra, and J. Querol. Skeleton-based agent development
for electronic institutions. In Proc. AAMAS’02, 2003.
17. J. Vázquez-Salceda. The Role of Norms and Electronic Institutions in Multi-Agent
Systems. Whitestein Series in Software Agent Technology. Birkhauser Verlag AG,
Switzerland, 2004.
18. J. Vázquez-Salceda and F. Dignum. Modelling electronic organizations. In
V. Marik, J. Muller, and M. Pechoucek, editors, Multi-Agent Systems and Applications
III, LNAI 2691, pages 584–593. Springer-Verlag, 2003.
19. M. Wooldridge, N.R. Jennings, and D. Kinny. The Gaia Methodology for Agent-
Oriented Analysis and Design. Autonomous Agents and Multi-Agent Systems,
3(3):285–312, 2000.
20. F. Zambonelli. Abstractions and infrastructures for the design and development of
mobile agent organizations. In M.Wooldridge, G.Weiss, and P. Ciancarini, editors,
Agent-Oriented Software Engineering II, LNCS 2222, pages 245–262. Springer-
Verlag, 2002.
21. F. Zambonelli, N. Jennings, and M. Wooldridge. Organisational abstractions for
the analysis and design of multi-agent systems. In P. Ciancarini and M.Wooldridge,
editors, Agent-Oriented Software Engineering, LNCS 1957, pages 98–114. Springer-
Verlag, 2001.
