About my research

         

My research interests are in the broad areas of Artificial Intelligence (AI) and Multi-Agent Systems (MAS). During my PhD and in the following years I have been working on intelligent autonomous agents reasoning and coordination, logic and argumentation-based dialogue and negotiation, specification and verification of agent interaction. In particular, I have been working on runtime monitoring and exception handling in interaction protocols, developing modeling frameworks to specify agent interaction using declarative tools such as backward and forward rules, the event calculus, and social commitments. Recent advances in norms for agent societies make me believe that much of the work done on interaction protocols and commitments may have a value also in the context of contract-based and normative multi-agent systems.

I did my best to promote Computational Logic and MAS research through the activities of the Italian Association for Logic Programming (GULP), with my involvement in the steering committees of the DALT and CLIMA workshops series, and by organizing the ISCL and DALT Spring Schools.

In these last years, I have been fascinated by the emerging field of computational social sciences, where I believe that a great deal of progress made in logical reasoning frameworks, especially argumentation-based, and multi-agent systems, can find promising application and have a positive impact on the society. I also believe that computer science research, such as that discussed at AAMAS, COMMA, IJCAI conferences and the like, has a lot to learn from other disciplines such as social and cognitive sciences, and philosophy (but it seems reluctant to admit it).

I am always open to collaborations. If you are interested in these topics and want to share ideas, feel free to drop me a line. I also encourage you to try out the software described in some of my publications:

The ALIAS architecture for distributed abductive reasoning, whereby agents can share hypotheses and reach conclusions in a collaborative fashion, using partial knowledge;

The SCIFF framework , for interaction protocol specification and verification. The SCIFF language is very simple and yet powerful: you can use it to specify the way you wish a system to behave, and then you can use the SCIFF proof-procedure to monitor at runtime whether the system does follow your specifications. You can express knowledge bases. SCIFF can be used in contexts such as multi-agent interaction and normative systems. SCIFF has been a joint endeavour between the AI group at the University of Bologna, and colleagues at the University of Ferrara (see below).

CLIMB, a specialization of SCIFF, somehow tailored to web service choreographies and business protocol specifications. CLIMB drew inspiration from work by Pesic and van der Aalst on Delare and ConDec. CLIMB's conceptual framework and implementation were mainly due to Marco Montali, currently in Bolzano;

jREC, a Java runtime monitor for open systems specified using REC, a reactive version of the Event Calculus, particularly apt to tracking fluents online. jREC has been implemented by Marco Montali;

 ComMon, a runtime monitor for multi-agent commitments. The commitment specification language, REC, allows you to specify properties that refer to a knowledge base, and reason with metric time, i.e., "real" deadlines (not just "next" or "until" and the like). That is why you should check it out if you want to develop practical applications (i.e., for diagnosing exceptions in multi-agent contracts) and you wouldn't mind doing that based on solid theoretical background. jREC has been implemented by Marco Montali;

 NetArg, a NetLogo model for agent based social simulations, in particular for studying opinion dynamics [check out this video]. NetArg agents are empowered with abstract argumentation frameworks and are meant to strike a good compromise between more basic, very common representation of opinions (e.g., an array of real values) and more complicated, but less popular BDI-like representations of cognitive agents. With NetArg we want to model not only the dynamics of opinions in social network, but also the reasons behind opinions, expressed as arguments. NetArg was mainly implemented by Simone Gabbriellini;

 TwitterArg, a NetLogo model for analyzing microdebates, i.e., streams of Tweets about a certain topic, tagged so as to mark opinions and relations between opinions. Arguments are built bottom-up around opinions, by grouping together Tweets about the same opinion. TwittterArg uses ConArg, a CP-based Java reasoner developed by Stefano Bistarelli and Francesco Santini, to compute the semantics of abstract argumentation frameworks in an efficient way. Arguments may have different weights, based on the number of Tweets or re-Tweets. NetArg was mainly implemented by Simone Gabbriellini.

The rest of this page mainly discusses my research activities up to 2006. For my more recent activities, check my publications, and those by my co-authors and by other authors interested in related topics.

Logic-based Multi-Agent Systems

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].

Impact of my research

According to Google Scholar, in April 2013 my H-Index is 22, my i10-Index is 42. Here there is an incomplete list of articles citing my work.


 

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 Last modified Tuesday, 24-Sep-2013 09:57:32 CEST