An Agent-based Framework for Multi-domain Service Networks

Eduroam Case Study

Ameneh Deljoo

, Leon Gommans

, Tom van Engers

and Cees de Laat

Institute of Informatics, University of Amsterdam, Amsterdam, Netherlands

Air France-KLM, Amsterdam-Schiphol, Netherlands

Leibniz Center for Law, University of Amsterdam, Amsterdam, Netherlands

Institute of Informatics, University of Amsterdam, Amsterdam, Netherlands

Keywords:

Normative Agents, Agent-roles, Service Provider Group, Story Animation, Petri Nets, Distributed Simulation

Models.

Abstract:

This paper introduces a methodology for the acquisition of the computational model of a service provider

group and its transformation into agent-based model. The methodology is as follows. First, we analyze the

case at the signal layer, i.e. the message exchange between actors, and model them with the components

of “belief, desire and intention (BDI)” agent architecture. In the next step, we identify the implicit actions,

intentions, and conditions which are necessary for the story to occur. These steps correspond to descriptions

of agent-roles observed in the case study. As a concrete result, a preliminary implementation of the framework

has been developed with Groovy.

1 INTRODUCTION

A priori identiﬁcation of beneﬁts and risks to stake-

holders that collaborate to provide a service across

multiple service domains is a problem that depends on

the goals, beneﬁts and capabilities of multiple service

providers. In this paper, we will explore the feasibility

of Agent Based Modeling(ABM) use as a ﬁrst step to

identify the beneﬁts and risk in such an open domain

system. ABM has been introduced to model an open

domain where agents are self-governed autonomous

entities that pursue their own individual goals based

only on their own beliefs and capabilities (Abdelka-

der, 2003). Open domain systems have an intuitive

mapping onto an ABM. An open domain system con-

sists of smart, cooperative and autonomous agents

where each of them has its own goal to achieve.

Agents present speciﬁc roles in this system and inter-

act with others as a means to accomplish their goals.

Modeling such systems receives considerable atten-

tion from both the Artiﬁcial Intelligence (AI) and the

communications network communities (Abdelkader,

2003; Dignum et al., 2005). ABM provides a way to

investigate the beneﬁts of collaborating autonomous

agents. A service network is an example of an open

system. Service networks are composed of competi-

tive service providers that see the beneﬁt in collabo-

ration. It is important to note that in such networks,

each member cannot provide a service on its own and

collaboration provides beneﬁts such as reduced cost

or increased revenue. For instance, providing authen-

ticated Eduroam WiFi access to visiting students is an

example of a campus IT service that a single univer-

sity is unable to provide on its own without having

a collaboration with other universities. The Service

Provide Group (SPG) (Gommans et al., 2015) is a

way to describe such collaboration. The SPG frame-

work provides a way to organize thinking about multi-

domain service network and can be used to describe

the structure of such a collaboration. Eduroam is a

good example of such collaborations. In this paper,

we take the Eduroam confederation as an example of

open domain system which consists of multiple au-

tonomous agents, where each of them have their own

goal and intent to collaborate.

ABM is an effective platform for the SPG because

they provide mechanisms to allow organizations to

advertise their goal, negotiate their terms, exchange

rich information, and synchronize processes at a high-

level of abstraction (Preece et al., 1999). A compre-

hensive model for ABM must be able to express the

global goal and the requirements of the domain in a

distributed way by considering the autonomy behav-

ior of the SPG.

Deljoo, A., Gommans, L., Engers, T. and Laat, C.

An Agent-based Framework for Multi-domain Service Networks - Eduroam Case Study.

DOI: 10.5220/0005821502750280

In Proceedings of the 8th International Conference on Agents and Artiﬁcial Intelligence (ICAART 2016) - Volume 1, pages 275-280

ISBN: 978-989-758-172-4

275

This paper aims at presenting an ABM for multi-

domain service network. We demonstrate the trans-

formation of a sequence of inter-agent interactions

into intra-agent characterizations. The paper is orga-

nized as follows. The methodology is introduced in

section 2. In section 3, we present our SPG case study.

We present it at the signal layer, deﬁning the topol-

ogy and the story line. In the following we show how

to enrich the previous representations with an inten-

tional layer, integrating institutional concepts as well.

In section 4 we provide elements for the transforma-

tion of the previous models into scripts for cognitive

agents. Discussion and further steps will be presented

at the end.

2 METHODOLOGY

The method we used to provide an ABM model of

a SPG is as follows: the case was analyzed at the

signal layer, i.e.we identiﬁed all the events and their

messages; then we visualized them by using a mes-

sage sequences chart (MSC). Next, we integrated the

previous layer with an internal behavioral characteri-

zation, a speciﬁcation and we constructed an agentic

layer where we addressed intentions of agents. For

this purpose, we deﬁned the mental objects and events

from a BDI perspective, maintaining the relationship

between components. Finally, we embedded an in-

stitutional layer to consider the normative aspect. It

should be noted that our conceptual framework covers

several realities: physical (message exchange), men-

tal (social network), institutional and story line.

3 Eduroam AS A SERVICE

PROVIDER GROUP

This study has been motivated by Leon Gom-

manse (Gommans, 2014), who is a researcher on

multi domain authorization frameworks. His SPG re-

search considers the role of trust and power to autho-

rize a service delivery by multiple autonomous ser-

vice provider. In general terms, Eduroam [EDUR]

allows students, researchers and staff from participat-

ing institutions to obtain Internet connectivity (WiFi)

across campus and when visiting other participating

institutions by simply opening their laptop. Eduroam

allows participating research and education institu-

tions, known as an eduroam SPG, to provide internet

access for students from any other participating insti-

tute that acts as Identity Provider (IdP). To reduce the

complexity of case study, we only consider one SP

Figure 1: Example of occurrence: a WiFi connection in-

stance.

(university) and students who are willing to use this

free service. In the following section, we describe the

story of Eduroam

Eduroam network is an example of

a SPG and works as follows:

A university offers a WiFi access to students

and staff who are registered in the Eduroam

identity database. The student accepts the

term and condition of this free service. The

university requests an identity from the stu-

dents. The student provides a valid identity.

Finally, the university will deliver the service

(free WiFi).

A successful WiFi connection is a fundamental cross

domain transaction. Consequently, what the case de-

scribes is a collaboration among the SPG (university)

and their users (students) which is just one of many

other possible scenarios. Figure 1 shows a successful

Eduroam connection process.

3.1 Signal Layer

In order to initiate the modeling, ﬁrst we look at the

speech acts of agents and all the events to illustrate the

ﬁrst layer of our framework (called signal layer). As

a ﬁrst deﬁnition, we may consider a story as a chain

of events which act as functions to bring the story

from a set of initial conditions to a certain conclusion

(from this perspective, we can consider all of them

as acts of communication, as messages going from

a sender to a receiver entity). In addition, each ac-

tion is coupled with the acknowledgment by the other

party. The Eduroam service delivery process is ba-

sically characterized by the actions offer, accept, re-

quest, provide and open access, performed by one of

the parties as represented in Figure 1. This process

is protected by an Eduroam confederation agreement,

when a mandatory action is not executed, the party

who was expected to beneﬁt from the act can enforce

on a failed performance. In order to trigger the perfor-

mance of the reported acts, there might be other con-

Eduroam is a federated roaming service that provides

such secure network access by authenticating a user with

their own credentials issued by their IdP. A group of Na-

tional Research and Education Networks (NRENs) are in

essence providing this service for their participating educa-

tional institutes under the eduroam brand arranged by TER-

ENA (L

opez et al., 2008; Wierenga and Florio, 2005; Gom-

mans et al., 2015).

ICAART 2016 - 8th International Conference on Agents and Artiﬁcial Intelligence

276

University

Student

Out

offer

Provide ID

deliver

Out

Provide ID

deliver(Access)

University

Out

out

offer

Deliver(Open Access)

Provide ID

Student

Figure 3: Topology of an Eduroam story: direct and indirect communications.

University

Student

offer

Deliver(Open Access)

Provide ID

request ID

Approved

Figure 2: Message sequence chart of a story about an

Eduroam WiFi service.

ditions or hidden acts to be taken into account. Thus,

the story can be illustrated in Figure 2. A student

usually accepts a term and condition only if he/she

holds a valid identity and physically presents at the

Eduroam WiFi range. To be Registered as a student

is a precondition for successfully perform the autho-

rization steps. Both physically presents and holds a

valid Id are examples of critical conditions for com-

pleting the process by this story. Such critical condi-

tions are in general associated to the ability or, more

in general, to the power of the agent, in a speciﬁc con-

text ”agent+environment”. They identify the proposi-

tions that should be true in the story-system, so that

the agent is successful in the performance of the asso-

ciated action.

3.2 Topology

The topology is drawn based on the collection of mes-

sages. The topology serves as a still picture of the

whole story-system, and shows how signals are dis-

tributed over the agent-roles (Boer and Van Engers,

2011). In our approach, topology helps to identify an

agent in a certain agent-role which is shown by the

MSC (e.g. Figure 2). This part of the research has

been inspired by an ”actor model” of (Hewitt et al.,

1973). For simplicity, we only consider two possi-

ble representations of the topology (direct and indi-

rect communication), which has been illustrated in

Figure 3. The ﬁgure’s right side, the little boxes are

messages queues and lines are communication chan-

nels. Also, all messages have a speciﬁc propositional

content. On the left ﬁgure, the dashed lines refer to

actions that have relevant outcomes besides the di-

rect communication. In order to take eventual side-

Figure 4: MSC with intentions and critical conditions.

effects into account, we introduced an explicit world

actor, dis-joining the sender from the receiver (which

is presented in the right ﬁgure). The world would play

as intermediary entity also in case of broadcast mes-

sages. In the Eduroam case, world plays as a role of

an IdP.

4 AGENT PERSPECTIVE

In the previous section we referred to the message ex-

change in this story (Eduroam WiFi access). When

we discover such messages, however, we apply an

intentional stance introduced by Dennett (Dennett,

1989). We started from a representation of the

Eduroam WiFi access story on the MSC chart and

we reﬁned it with Petri nets patterns. Beside that we

want to extract agent-role descriptions from this rep-

resentation. Therefore, we write down typical scenar-

ios (e.g. Figure 1) with the typical roles that agents

play. Such roles are associated with certain beliefs,

plans (resulting in actual actions) and goals. An agent

is able to play simultaneously several roles and vice-

versa. From the agent point of view, the precondition

and ex-post intentional interpretation of the story re-

sults in a decomposition of the plans followed by the

agents. A possible result of the interpretation is pre-

sented in Figure 4. In order to do so, ﬁrst externalized

intents have been considered as the events triggering

the processes of offer/open access between a univer-

An Agent-based Framework for Multi-domain Service Networks - Eduroam Case Study

277

sity and a student. The ﬁnal results of those actions

are then reported with output messages at the end of

the chart. In the next step, we consider the possible

hidden acts. In this case, we know that the univer-

sity usually accepts student’s requests for using the

WiFi, once their identities have been approved by the

IdP. And ﬁnally, we use the critical grouping to high-

light conditions (in addition to sequential constraints),

which are necessary for the production of that mes-

sage. To sum up, we assume that: (a) the student per-

forms an evaluation of the offer (evaluation action),

(b) the student accepts the offer if it is acceptable for

him/her (term and acceptability condition), and (c)

the student provides the ID (the university provides

access) if he owns the requested information (valid

identity or ownership condition). The MSC diagram

in Figure 4 depicts a good conclusion for the story;

the inputs/outputs provide an intentional characteriza-

tion. The vertical bars indicate the ongoing activities,

while the messages refer to successful acts of emis-

sion and reception, whose occurrence is constrained

by the critical conditions. In the following sections

we will introduce some patterns to be attached to the

ﬂow of the story. Instead of using just one visualiza-

tion, we provide alternative representational models.

In our model, we refer to four layers, each of which

addresses speciﬁc components:

• the signal layer—acts, side-effects and failures

(e.g. technical failure,user abuse): outcomes of

actions,

• the action layer—actions (or activities): perfor-

mances intended to bring about a certain result,

• the intentional layer—intentions: commitments to

actions, or to build up intentions,

• the motivational—motives: events triggering the

creation of intentions.

The last three layers compose the agentic layer. The

closure of the sensing-acting cycle of the agent is

guaranteed by the fact that certain signals, when per-

ceived by agents, becomes motives for action. In our

framework, motivation refers to conditions that makes

the agent sensitive to a certain fact, which becomes

the motive for starting an action. As we observed be-

fore, obligations are prototypical reason for actions.

Despite of that, not all obligations are followed by a

performance. People comply with obligations when

they have some motivation due to habit, convenience,

respect for authority, or in our case to use WiFi. Mo-

tivations however often remain implicit in the story

(Sileno et al., 2013).

4.1 Institutions

In general, we can say that an institution is an inten-

tional social collective entity (Boer, 2009), deﬁned by

certain rules and some institutional facts. It is col-

lective and intentional, simply because a group of

people recognizes its existence. A complementary

perspective on institutions has been introduced by

Searle (Searle, 1969), and more recently by (Searle,

2009), as an outgrowth of his study. This concept of

institution uniﬁes games, (social) informal norms and

legal norms. Terms like ”university” and ”student”

denote agents acting within the free WiFi institution.

However, there is an intrinsic difference between the

actual participants and the role that they play. An

institution concerns persons, but not whole persons:

each one enters via an adequately trained and special-

ized part of himself. These parts are embodying spe-

ciﬁc institutional roles.

Agent-role model were ﬁrst introduced by Boer

and Van Engers (Boer and Van Engers, 2011) with

the purpose of representing scenarios of compliance

and non-compliance elicited from legal experts. In

this work, an agent-role links the concepts of institu-

tional role, and intentional agent. In practice, we add

characteristics to the role that are important factors

according to the constructed normative theory, and

we describe its behavior by using an intentional ap-

proach. We start considering only the core functions

(events, acts) related to our character. This process

proceeds by using a common knowledge interpreta-

tion to deﬁne each agent’s intention. Then, the anal-

ysis of intentions allows us to reconstruct the goal

reduction process. Rationality is usually deﬁned as

the ability of an agent to construct plans of actions

to reach the goal. Differently from objects (and ac-

tors), however, agent-roles are entities associated also

to motivational and cognitive elements like desires,

intents, plans, and beliefs.

Institutional roles are deﬁned with certain abilities

(equivalently, powers), obligations and expectations

about the other roles. Following the description given

by the Eduroam WiFi agreement, if a student accepts

an offer, and if he/she does that, he/she has to provide

a valid ID, to expect an access to the WiFi from any

other participating institute (universities) that acts as

an IdP provider. Therefore, institutional roles are de-

ﬁned in the ﬁrst place by actions that may be taken, in

an adequate institutional setting, in order to achieve

certain goals. Furthermore, we observe that the pos-

sibility of WiFi connection exists because there is a

university who has offered and received acceptance

and ﬁnally delivers the service. Both roles are strictly

necessary: there cannot be a student without a univer-

ICAART 2016 - 8th International Conference on Agents and Artiﬁcial Intelligence

278

Figure 5: A WiFi connection transaction illustrated in terms of actions, with pre- and post conditions.

Figure 6: Full action pattern associated to an Eduroam WiFi connection.

sity in case of free WiFi. In this line of thought, WiFi

connection does not concern only one university with

its own students. Eduroam connection is a free WiFi

for all students all over the world and composed by

several competing actors (e.g. campuses). Although,

it is not explicitly present in the formal description of

the internet connection institution, the presence of IdP

and technical partners is obviously not negligible for

the institutional role. These relations are involved in

the evaluation of the offer (having a power to offer as

a university) and action which meant to judge the ac-

ceptability of the offer (being in the WiFi range and

holds a valid ID). Evaluation however, is not made

explicit in the deﬁnition of the free WiFi process. A

complete scheme about the process can be drawn uni-

fying procedural and institutional descriptions which

have been shown in Figures 5, 6. The university acts

as offeror and student acts as offeree. The gray circle

in Figure 5 shows that the performance of the action is

not sufﬁcient to proceed, but it has to return a positive

result.

4.2 Visualization

We use Petri nets to visualize the ﬂow of the

story (Fehling, 1993). The choice of Petri nets as rep-

resentational model has positive outcomes in itself.

First, allowing for descriptions in terms of localized

states rather than a global state comparable to Kripke

models(Esakia, 1974). Next, exploiting their topo-

logical characterization, can easily model the institu-

tional dynamic, i.e. timing/synchronization aspects.

Finally, Petri nets offer a direct visualization both of

the local structure and of the behavior of the system,

which can be useful for validation purposes.

4.3 Preliminary Implementation

For the model discussed in Figure 6 we have imple-

mented a generic framework in Groovy. Groovy is a

recent extension of Java which compiles on the Java

virtual machine (JVM). The language is suitable for

fast prototyping, and differently from Java, is a dy-

namic language, and can be used for scripting. It

provides the libraries implementing the actor compu-

tational model as described by Hewitt et al. (Hewitt

et al., 1973). This framework is able to take care

of all the parallel and concurrent actions that need to

be done in the case study. The Default-Actor class

was provided to be the base for our agent class. This

Agent class can be used to further implement differ-

ent agent roles and the interaction between them. For

space reasons, we are not able to present further ex-

amples of their use with Petri net models and source

code, but the interested readers can ﬁnd some other

models on our website

and more information about

the project on our website

https://sarnet.uvalight.net/

http://delaat.net/sarnet/index.html

An Agent-based Framework for Multi-domain Service Networks - Eduroam Case Study

279

5 DISCUSSION AND FURTHER

DEVELOPMENTS

Our research is intended to model normative reason-

ing in a complete distributed environment. In par-

ticular, we are interested in how to model the SPG

from the normative perspective to observe the agent

behavior and identify the beneﬁts and risks. In the

current approach, typical strategy decision problems

for a given game do not take explicitly into account

the possibility of the player to behave avoiding a rule,

or forcing the interpretation of the rule toward its in-

terest, if the regulator (consciously or not) left some

ambiguity. Using our framework, agents models or

roles involved in a social scenario, outlined from a

story can be described. As an operative result, such a

simulation can help to understand the social (institu-

tional) dynamics: validating the domain of conceptu-

alization of the experts, making predictions, suggest-

ing improvements to regulations for the SPG frame-

work and spotting normative weaknesses and vulner-

abilities. This model is an essential step to provide

an ABM of cross domain framework which is one of

the directions of our future research. Along with this

work, a preliminary implementation has been devel-

oped, using an existing ABM platform. The current

ABM implementation was expressive enough to build

a ﬁrst version of the generic ABM framework of SPG.

However, we have experienced some shortcomings in

expressivity, which are left outside the scope of this

paper, and we will address these issues as next steps

and present in a separate publication.

ACKNOWLEDGEMENTS

We would like to thank the Netherlands COMMIT/

program and NWO organization for making this re-

search possible. We also like to thank KLM for pro-

viding guidance and the context for this research.

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