information provided by human developers is crucial
for classification and enhancement of concepts.
However, to obtain real semantics, we believe that a
better approach would also consider the pragmatic
usage of communication primitives in the
communication protocol.
In this paper we present a pragmatic approach for
aligning communication primitives, considering
their usage in the protocol. To evaluate our solution
we compare the resulting relations and show that our
approach provides more information for relating
communication primitives.
The rest of the paper is organized as follows. In
section two we present related work with the subject
of this research. In section three we describe the
general procedure for aligning communication
protocols. In section four we present a case study to
show the applicability of our approach. In section
five we evaluate the results and finally, in section six
we conclude.
2 RELATED WORK
The problem of communication interoperability in
MAS represents a common topic, which has been
researched from different perspectives. (Guido et al.,
2006) presented a common ontology of agent
communication languages to bridge the gap between
two approaches of defining semantics: mental
attitudes and social commitments. (Fourlan de Souza
et al., 2001) defined the problem of interoperability
and presented Saci (Simple Agent Communication
Infrastructure), a tool for programming
communication among distributed agents and a
CORBA bridge to overcome the interoperability
problem. (Labrou et al., 1999) described the
interoperability problem between agents. They
stated that any solution should take into
consideration three aspects: a) various languages,
representing different programming paradigms, b)
different hardware platforms and operating systems,
and c) few assumptions about the internal structure
of agents. They also described two possible layers of
solutions: translation between languages and
guaranteeing that the semantic content is preserved
among applications. (Chaib-Draa, 2002) presented
the related work and trends on semantics of ACL, he
compared the semantics of KQML and FIPA-ACL,
and identified that in both cases communicative acts
are described in terms of beliefs, intentions, desires
and similar mental states. Finally he concluded that
agents are almost never programmed using such
mental states directly. Therefore it is almost
impossible to verify whether the messages are used
correctly by the agents and the link between theory
and practice in ACL use is still very big.
To solve the problem, the most common solution
reported in literature consists of defining and using a
shared ontology and a translation approach between
the different ACL implementations. But the
implementation of such a solution requires a human
expert to analyze and compare among those ACL
implementations to discover and define relations
among primitives. In this specific task many authors
have presented different techniques and algorithms
for aligning and matching vocabularies in various
research areas, such as data base schema integration,
knowledge engineering, natural language processing
and information systems integration. In data base
research (Rahm, 2001) argues that “match” is a
fundamental operation to manipulate data schemas,
which takes two schemas as input and produces a
mapping between elements that correspond
semantically each other. (Batini, 1986) presented
various data base schema integration methods and
established three integration phases: schema
comparison, schema conforming and schema
merging. In the area of knowledge engineering
various methods have been proposed. Chimaera
(McGuinness, 2000) is a semi-automatic merging
and diagnosis tool developed by the Stanford
University Knowledge Systems Laboratory. It
provides assistance in the task of merging
knowledge bases produced by multiple authors in
multiple scenarios. PROMPT (Noy, 2000) is an
algorithm that provides a semi-automatic approach
to ontology merging and alignment. PROMPT
determines possible inconsistencies in the ontology,
which result from the user actions, and suggests
ways to remedy these inconsistencies.
In the above related works we can see a common
concern in the problem of communication
heterogeneity in MAS. We can appreciate also that
there are many aspects in communications that can
cause heterogeneity. Various authors have reported
solutions based on the incorporation of ontologies,
and the need for aligning concepts from different
sources. Aligning is a task that depends on the
provided semantics of communication primitives,
but due to different implementations of agents, such
semantics may differ from one agent to another. In
this work we are dealing with communication
protocols, where documentation of primitives is
generated during development time. We take as
input those descriptions and extract keywords to
generate classifications according to the type of
primitive. After classification we compare such
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