Artificial Intelligence and Knowledge Representation

Resarch lines:

  • Description Logics
  • Reasoning about Actions
  • Semantic Web
  • Logics for AI
  • Cognitive Robotics


Members:
Luigia Carlucci Aiello (leader), Giuseppe De Giacomo, Maurizio Lenzerini, Paolo Liberatore, Domenico Lembo,
Daniele  Nardi, Fiora Pirri, Riccardo Rosati, Marco Schaerf.

Ph D. Students: 


Riccardo De Masellis, Paolo Felli, Mario Gianni, Matteo Leonetti, Gabriele Randelli, Domenico Fabio Savo.

Post Docs:
Marco Ruzzi, Vittorio  Amos Ziparo.

 

Research in Artificial Intelligence at DIS started in the early 80s and established this research group as one of the most prominent ones in the field of logic-based knowledge representation and automated reasoning. Research  has been conducted in many areas, with several outstanding results. The research lines presently active are described in the following.

Description Logics (DL) form a family of Logic-based Knowledge Representation Languages which allow for modeling an application domain in terms of objects, concepts and relationships between concepts, and for reasoning about them. They are widely used in several areas, including ontology engineering, Semantic Web, and information integration. The research at DIS on DL has a long tradition, and focuses on many relevant aspects, including algorithms for automated reasoning, trade-off between expressive power and computational complexity of reasoning, query answering in DL knowledge bases, adding both monotonic and non-monotonic rules to DL. In the future, the work on DL will both continue along the above mentioned lines and focus on dynamic aspects, such as update and revision of DL knowledge bases, and reasoning about programs expressed on such knowledge bases.

Reasoning about Actions concerns the theory and the implementation of agents that reason, act and perceive in changing, incompletely known, and unpredictable environments. Such agents must have higher level cognitive functions that involve reasoning, for example, about goals, actions, when to perceive and what to look for, the cognitive states of other agents, time, collaborative task execution, etc. Our research on Reasoning about Actions focuses on several aspects, including: foundations of theory of actions; various forms of planning for sophisticated dynamic properties, e.g., expressed in LTL; high-level agent programs, like ConGolog based on the Situation Calculus; agent behavior synthesis and composition. This research is also related with, and applied to, other areas, such as cognitive robotics, multi-agent/multi-robot systems, software service modeling, execution and composition, high-level programs over ontologies and data sources.

The Semantic Web aims at intelligent information processing by creating and connecting a web of machine-understandable information. Our research in this area mainly focuses on representation languages for the Semantic Web, in particular, ontology specification languages. A remarkable outcome of our research in this area is the standardization (October 2009) of the OWL 2 QL ontology specification language by the World Wide Web Consortium. OWL 2 QL directly derives from DL-Lite, a family of ontology formalisms which we proposed and studied in our recent research in this field.

Another research strand is focused on belief revision (how to revise knowledge when new information is given), default logic (how to draw inference in case precise information is lacking), and automated planning.

Finally, one research stream specifically addresses action representation and world modeling in intelligent robots, also in connection with the work in Multi-Agent and Multi-Robot Systems. The goal is to bridge the gap between the theoretical work in knowledge representation and reasoning and the design of intelligent robotic systems.

Projects:
TONES Thinking Ontologies 
September 2005 - December 2008  -   EU FP6

Projects managed by ISTC-CNR
(National Research Council)

ROBOCARE: ROBOtics for the CARE of elderly and disable people
2003 - 2007  MIUR

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