=Paper=
{{Paper
|id=Vol-223/paper-9
|storemode=property
|title=Effective Use of Organisational Abstractions for Confidence Models
|pdfUrl=https://ceur-ws.org/Vol-223/13.pdf
|volume=Vol-223
|authors=Ramón Hermoso (University Rey Juan Carlos),Holger Billhardt (University Rey Juan Carlos),Roberto Centeno (University Rey Juan Carlos),Sascha Ossowski (University Rey Juan Carlos)
|dblpUrl=https://dblp.org/rec/conf/eumas/HermosoBCO06
}}
==Effective Use of Organisational Abstractions for Confidence Models==
https://ceur-ws.org/Vol-223/13.pdf
Effective Use of Organisational Abstractions for Confidence Models1
Ramón Hermoso Holger Billhardt Roberto Centeno Sascha Ossowski
Artificial Intelligence Group, DATCCCIA, University Rey Juan Carlos
C/Tulipán s/n, 28937, Móstoles (Madrid), Spain
{ramon.hermoso, holger.billhardt, roberto.centeno, sascha.ossowski}@urjc.es
1 Introduction
Trust and reputation systems are not only useful for Virtual Organisations (VOs), but VOs also
for trust and reputation mechanisms. The structure provided by a VO can be used to construct
more effective trust mechanisms. In particular, the structural elements defined in a VO (e.g., roles
and interactions) provide a certain notion of similarity which allows agents to infer the expected
behaviour of acquaintances within new situations by analysing their past behaviour within similar
situations. This property is especially useful in situations where agents do not yet have sufficient
experiences related to a specific type of interaction, or within very volatile environments.
In this paper [1] we continue our previous work [2] on trust mechanisms for VOs. We present
some experiments that show how the use of organisational abstractions can effectively improve trust
mechanisms. We also put forward a testbed developed to compare trust models in VOs (TOAST).
2 Confidence and Trust for Organisational Structures
As outlined in [2], it is natural to consider that agents participating in a VO play some roles in
different interactions. In addition, we assume that the agents know the organisational structure,
e.g., they know the existing roles and interaction types, the roles that participate in each interaction
type, as well as the roles other agents are playing within the organisation.
Similarly to other approaches [3, 4], we build our trust model on the idea of confidence and
reputation. Both are ratings agents use in order to evaluate the trustworthiness of other agents
in a particular issue (e.g., playing a particular role R in a particular interaction I). Confidence –
cA→hB,R,Ii , confidence that agent A has on agent B playing role R in interaction I – is a local
measure that is only based on an agent’s own past experiences, while reputation is an aggregated
value an agent gathers by asking its acquaintances about their opinion regarding the trustworthiness
of another agent. Thus, reputation can be considered as an external or social measure. We define
trust – tA→hB,R,Ii – as a rating resulting from combining confidence and reputation values.
Agents will accumulate their previous experiences in their internal structures we call local in-
teractions table (LIT). When only a few experiences have been performed previously, classical
approachs suggest to use reputation mechanisms in order to gather opinions about trust others
have about a third party. However, this view poses some problems, namely opinions from ma-
licious agents. Thus, our approach proposes agents to take into account similiar past situations
in order to infer behaviours of others [2]. This approach relies on the hypothesis that, in general,
agents behave in a similar way in all interactions related to the same role. We argue that, exploiting
this idea, the more similar I ′ and I are, the more similar the values cA→hB,R,I ′ i and cA→hB,R,Ii will
be. The same applies to roles. Using this assumption, confidence ratings accumulated for similar
agent/role/interaction tuples may provide evidence for the trustworthiness of the issue hB, R, Ii.
Based on this idea, we propose to build trust by taking into account all the past experiences an
agent has, focusing on their degree of similarity with the issue hB, R, Ii. In particular, we calculate
1 The present work has been funded by the Spanish Ministry of Education and Science under project TIC2003-
08763-C02-02.
trust as a weighted mean over all the confidence values an agent has accumulated in its LIT. This
is shown in the following equation:
P
cA→hX,Y,Zi · rA→hX,Y,Zi · sim(hX, Y, Zi, hB, R, Ii)
hX,Y,Zi∈LITA
tA→hB,R,Ii = P (1)
rA→hX,Y,Zi · sim(hX, Y, Zi, hB, R, Ii)
hX,Y,Zi∈LITA
where the entries in agent A’s LIT are used in order to estimate the confidence agent A has
on issue hX, Y, Zi by combining confidence reliability (rA→hX,Y,Zi ) and the similarity of the issue
hX, Y, Zi to the target issue hB, R, Ii. We suppose that organisational models include information
from which issues similarities can be derived.
3 Trust Organisational Agent System Testbed (TOAST)
TOAST is a tool we have developed in order to test our proposed model and to provide evidence
that our assumptions are correct. TOAST evaluates the influence of different trust models on the
evolution of the overall utility of an agent or a society of agents. This testbed simulates a virtual
organisation where agents have to interact with others in order to achieve their goals. In our
experiments we used a virtual organisation with 20 agents (with same behaviour) and the testbed
generated randomly 40000 goals for those 20 agents. We have tested three different models: a
random model, a past history-based model and our inference model based on similarities. The
results confirm that the use of organisational structures makes agents’ decision-making easier and
more efficient, in particular when agents have very few previous experiences within the organisation.
4 Conclusion
In this paper we have presented results of our work, aimed at integrating trust mechanisms into
virtual organisations. We have tackled the problem of locally calculating trust, that is, finding
“good” counterparts, even if only very few previous experiences are available and without the need
of using reputation information obtained from external sources. The proposed model takes into
account key concepts of organisational models, such as roles and interactions. It has confidence
inference capabilities exploiting organisational structures provided by VOs. We have tested our
model, confirming that the use of organisational structures makes agents’ decision-making easier
and more efficient, in particular when agents join an organisation and, thus, can not count on
their own previous experiences. Furthermore, we have presented TOAST, the testbed that we have
developed to test our assumptions.
References
[1] Ramón Hermoso, Holger Billhardt, Roberto Centeno, and Sascha Ossowski. Effective use of
organisational abstractions for confidence models. In Michael O’Grady Oguz Dikenelli Gre-
gory O’Hare, Alessandro Ricci, editor, 7th Annual International Workshop Engineering Soci-
eties in the Agents World, pages 246–261, September 2006.
[2] Ramón Hermoso, Holger Billhardt, and Sascha Ossowski. Integrating trust in virtual organi-
sations. In AAMAS-06 Workshop on Coordination, Organization, Institutions and Norms in
agent systems (COIN), pages 121–133, 2006.
[3] T. Dong Huynh, Nicholas R. Jennings, and Nigel R. Shadbolt. FIRE: An integrated trust and
reputation model for open multi-agent systems. In Proceedings of the 16th European Conference
on Artificial Intelligence (ECAI), 2004.
[4] Jordi Sabater and Carles Sierra. Reputation and social network analysis in multi-agent systems.
In AAMAS ’02: Proceedings of the first international joint conference on Autonomous agents
and multiagent systems, pages 475–482, New York, NY, USA, 2002. ACM Press.