MAS are communities of problem-solving entities that can perceive and act
upon the environment to achieve their individual goals as well as joint
goals. Work on such systems integrates many technologies and concepts in
AI and other areas of computing as well as other disciplines. Over recent
years, the agent paradigm gained popularity, due to its applicability to a
full spectrum of domains, from search engines to aids to electronic
commerce and trade, e-procurement, recommendation systems, distributed
diagnosis, simulation and routing, knowledge management and distributed
systems configuration. In such domains, a centralized approach based on a
single solver in charge of managing all aspects of a distributed
computation would be inadequate. A multi-agent approach, instead, seems to
be more promising in that it would allow for collaboration of multiple
solvers, which will coordinate with each other and exhibit autonomy of
reasoning and decision making in solving relevant sub-tasks.
Although commonly implemented by means of imperative languages, mainly for
reasons of efficiency, agent-related concepts have recently increased
their influence in the research and development of computational
logic-based systems [AMAI 2004].
Computational logic provides a general framework for studying syntax,
semantics and procedures for agents. Besides, it lends itself to the
specification and verification agent interaction, and to the
implementation and description of environments, tools, and standards for
MAS.
In the context of logic-based MAS, my research activity has focussed on
three main aspects: coordination of agent reasoning, agent negotiation,
and agent interaction.
Co-ordination of agent reasoning
One of the main engineering principles of MAS is locality. Each agent is
responsible for operations within a limited domain, and will base most of
his reasoning on domain-specific knowledge. However, when many agents
interact with each other, each one operating based on its own knowledge
and beliefs, it may become necessary for agents to take into account
information and results produced by other agents. It is then necessary to
extend classical reasoning techniques so as to enable agents to cope with
multiple and incomplete knowledge, and to interact with each other, for
information sharing and possibly for consistency maintenance purposes. In
this context, abduction is a well known hypothetical reasoning mechanism
in AI aimed at explaining observations or guessing causes of effects,
based on an incomplete knowledge.
Agents characterised by exhibiting abductive reasoning capabilities are
called abductive agents. Since my doctoral research activity started
[PhD 2002], I have been investigating different interaction patterns for
abductive agents. I have been working on extending existing abductive
logic programming-based proof-procedures towards multi-agent reasoning and
on the application of the developed techniques to different scenarios.
Among the main results achieved in this direction are the Abductive LogIc
AgentS architecture (ALIAS) presented in [AMAI 2003], and the
language LAILA, defined in [AIxIA Notizie 2000,CompLang 2001] to coordinate the
reasoning activity of multiple abductive agents. I have contributed to the
implementation of ALIAS and LAILA [ALIAS,AIxIA 1999], and to
their testing in several application domains, including negotiation over
resources [AMAI 2003], distributed diagnosis [CLIMA 2000],
recommendation systems [COCL 1999,MAS-LP 1999], judicial
evaluation of criminal evidence [AAIJ 2004].
Finally, I have contributed to extending ALIAS/LAILA towards coordination
of constraint-based reasoning in agent systems
[JELIA 2002a,AAMAS 2002a].
Logic and argumentation-based negotiation
Negotiation for resource achievement is one of the most
extensively studied areas in multi-agent research. It has been approached
from many perspectives, including game theory, auction theory, and more
recently argumentation. Many agent architectures and frameworks for
negotiation are only theoretical studies or practical implementations.
The main aims of my work on logic- and argumentation-based negotiation
have been to provide a well-specified, general purpose agent framework,
with a rigorous operational semantics defined to bridge the gap between
specification and implementation. Following Kowalski and Sadri's
pioneering work, "From Logic
Programming Towards Multi-Agent Systems" [AMAI 1999], my colleagues and I have identified abduction as the
main form of reasoning to reconcile knowledge coming from the outside of
agents (through negotiation) with internal goals and needs.
I pursued this work mainly in collaboration with the Agents and Logic
Programming groups of Imperial College London and of the University of
Cyprus. I started working on the definition of an argumentation-based
agent dialogue framework [AISB 2001] during a research visit to Imperial
College London in 2000. We understood that most available
argumentation-based negotiation proposed abstract frameworks, in which
agents were not implemented but only represented by their knowledge bases.
Protocols were mostly implemented by data structures based on state
automata. Considering abduction as an inference mechanism able to support
argumentation processes, we proposed a new approach based on abductive
logic agents [ATAL 2001], which gained a best paper award at a
prestigious event (ATAL). Since 2001, such a framework has been refined
and extended in several directions, and presented at the main AI, logics,
and agent conferences
[ECAI 2004,AAMAS 2002b,IJCAI 2003,JELIA 2002b] and workshops
[ESAW 2001,UKMAS 2002a]. Based on the seminal work of 2000 and
2001, I have actively contributed to the preparation and writing of a
European project proposal, which has been accepted in Fall 2001. From
2002 to 2005, my research activity has mainly focussed on the goals of the
EU-funded "Societies Of ComputeeS" project [SOCS], especially for what
concerns specification and verification of agent interaction.
Agent interaction: specification and verification
Agent Communication Languages (ACL) and Interaction Protocols (IP) are
generally defined for heterogeneous agents to effectively co-operate with
each other. The study of ACL and IP represents nowadays a major research
direction in MAS, and they are well known for being a well suited domain
for formal approaches. The two major schools of thought in this area tend
to interpret agent communication either from a motivational and causal
perspective, or from a social and open perspective, The former aims to
link the semantics of agent interaction to some agent architecture,
grounded on the notion of mental states, whereas the latter seeks to keep
such semantics independent of the agents' internals, and "open" to its
application to societies of heterogeneous autonomous agents. Following
this second main stream, the SOCS social model developed within the SOCS
project, to which I have actively contributed, has been firstly presented
[UKMAS 2002b] in association with deontic categories of social obligation
and commitment.
During the course of the SOCS project, I have worked on the definition of
the SOCS social model in terms of declarative semantics, initially with a
deontic flavour [CEEMAS 2003,FAMAS 2003], and subsequently with an
abductive interpretation [AIxIA 2003], and in terms of operational
semantics [AIxIA 2005,GC 2004,CLIMA VI,DEIS-LIA-06-001]. I have
contributed towards the implementation of the SOCS social model, called
the "SOCS Social Infrastructure" (SOCS-SI)
[SOCS,AAIJ 2006,AT2AI 2004,AAMAS 2004]. Finally, I
have contributed to investigating the application of SOCS-SI to a range of
domains. Among them, I have considered protocols for resource sharing
[DALT 2003], combinatorial auction protocols
[CISI 2004,Intelligenza Artificiale 2005], protocols for electronic transactions
[SAC 2004] and other protocols including human-to-human
e-mail-based IP and security protocols [ESAW 2005]. Recently my group
and I provided a mapping of the SOCS social model onto deontic and
normative frameworks [CMOT 2006], we extended the SOCS-SI framework
towards automated verification of agent interaction
[ENTCS 2003], and we started the development
of a methodology for protocol design whose main driver is property
achievement [WETICE 2004].
Other work
Alongside my research on Logic-Based MAS, I have also contributed to the
area of generative and reactive planning
[ISMIS 2000,UK PS-SIG 1999] in collaboration with the constraint
programming group of DEIS. Together with colleagues, I have investigated
the combination of logics and meta-heuristics for multi-agent resource
allocation [STAIRS 2002]. Finally, I have worked on the implementation
of abductive proof-procedures using Constraint Logic Programming
[AGP 2003,CILC 2004], and to the definition of new models
of agent interaction and information sharing
[CLIMA IVa ,CLIMA IVb].
Current research directions
My current research activity focusses on declarative specification and
formal verification of MAS, especially in relation to agent interaction.
Recent work done within the SOCS project has shown a great potential in
declarative technologies and computational logic-based approaches. I am
interested in defining a unified and open framework for MAS specification,
deployment, verification, based on computational logic and argumentation theories, and its
application to artificial societies, ambient intelligence, elder care and
e-care, cognitive systems, information management, and web services
choreographies.
Impact of my research
According to PublishOrPerish, to date (Sep 2011) my H-Index is 20, my G-Index is 32. Here there is an incomplete list of articles citing my work.
