Dipartimento di Informatica

Insegnamenti

• Data Science and Circular Economy
  PhD Programme in Innovation for the Circular Economy
• INFORMATICA II B (MAT0108)
  Scuola Universitaria Interdipartimentale in Scienze Strategiche (SUISS)
• Informatica I (CPS0501)
  Scuola Universitaria Interdipartimentale in Scienze Strategiche (SUISS)
• Reasoning about ontologies, causality, preferences, for explainability, accountability and compliance (INF01)
  PhD in Computer Science
• Reti di calcolatori (INF0150)
  Scuola Universitaria Interdipartimentale in Scienze Strategiche (SUISS)

Temi di ricerca

Gian Luca Pozzato was born in Moncalieri (Turin) in 1978. 
He took his ``Laurea'' degree ``summa cum laude'' in Computer Science in April 2003, and his Ph.D. in Computer Science in February 2007, both at the University of Turin, Italy. Since November 2015 he is an associate professor at the Department of Computer Science in the Università degli studi di Torino, where he is member of the "Knowledge representation, Automated Reasoning, Logic and ontologies" (KARL)  group.

His PhD dissertation "Proof Methods for Conditional and Preferential Logics" has been awarded by the Italian Association for Logic Programming (GULP) with the "Marco Cadoli" price, as one of the best two Phd thesis focused on computation logic and discussed between 2007 and 2009. Visit GULP page

His main research interests include non-monotonic reasoning, non-classical logics (in particular, conditional and preferential logics), non-monotonic extensions of description logics, and logic programming.

Conditional logics have a long history, and recently they have found interesting applications in several areas of artificial intelligence, including belief revision and update, the representation of causal inferences in action planning, the formalization of hypothetical queries in deductive databases. Conditional logics have also been applied to non-monotonic reasoning. A fundamental contribution to the study of the relation between conditional logics and non-monotonic reasoning has been given by Kraus, Lehmann and Magidor, who have introduced the so called KLM framework. The KLM framework has been introduced in order to describe a set of properties that any concrete non-monotonic reasoning system should satisfy. The logics of this framework are called preferential logics.

The family of Description Logics (DLs) represents one of the most important formalism of knowledge representation. DLs have a well-defined semantics based on first order logic and offer a good trade-off between expressivity and complexity. Since the very objective of a DL knowledge base is to represent a taxonomy of concepts, the need of representing prototypical properties and to reason about inheritance with exceptions easily arises. Standard DLs do not allow to reason about defeasible properties. His recent research is focused on extending standrd DLs with a typicality operator, in order to define defeasible properties and to reason about eceptions.

 

Gruppi di ricerca

• AI research @ Dipartimento di Informatica
• Knowledge representation, Automated Reasoning, Logic and ontologies
• Social Computing (SoCom)

• AI research @ Dipartimento di Informatica
• Rappresentazione della conoscenza, ragionamento automatico, logica e ontologie
• Social Computing

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Organi

• Consiglio di Dipartimento

Ricevimento studenti

Lunedì 10-12 oppure su appuntamento (dal 18/07/2014 *esclusivamente su appuntamento*) - Ufficio 3N - Dipartimento di Informatica - corso Svizzera 185 - 10149 Torino