Foto del docente

Paolo Torroni

Associate Professor

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems


Keywords: argumentation mining interaction protocols multi-agent systems agent-based simulation multi-agent dialogue logic programming hypothetical reasoning abductive logic programming argumentation opinion dynamics in social networks

My research interests are mainly in areas of Artificial Intelligence. 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.

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 interested in 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, can learn a great deal from other disciplines such as social and cognitive sciences and philosophy.

Among most recent interests, argumentation mining where I've been working with Marco Lippi, is concerned with the detection of argument from text in various genres and from speech. We have developed the first online argumentation mining system, available as a prototype on the MARGOT home page.

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.

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