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Speaker(s): Dr Nicola Gatti
Organiser: Dr Enrico H Gerding
Time: 06/07/2009 13:00-14:00
Location: B32/3077

Abstract

Game theoretic approaches to patrolling have become a topic of increasing interest in the very last years. They mainly refer to a patrolling mobile robot that preserves an environment from intrusions. These approaches allow for the development of patrolling strategies that consider the possible actions of the intruder in deciding where the robot should move. Usually, it is supposed that the intruder can hide and observe the actions of the patroller before intervening. This leads to the adoption of a leader-follower solution concept.

In this work, mostly theoretical in its nature, we propose an approach to determine optimal leader-follower strategies for a mobile robot patrolling an environment. Differently from previous works, our approach can be applied to environments with arbitrary topologies.

Speaker Biography

Dr Nicola Gatti

Nicola is an Assistant Professor of Computer Science in the Dipartimento di Elettronica e Informazione at the Politecnico di Milano, where he carries out research into the theory and practice of artificial intelligence and multiagent systems, in collaboration with the Artificial Intelligence and Robotics Larobatory. Currently, he is teaching Computer Systems, Algorithmic Game Theory, and assisting with Artificial Intelligence and Multi-Agent Systems.

He received his Laurea degree in Biomedical Engineering in June 2001 from the Politecnico di Milano and his PhD degree in Computer Engineering in March 2005 from the Dipartimento di Elettronica e Informazione at Politecnico di Milano. His work focuses on the area of multiagent systems; precisely, on game theory, multiagent planning, and multiagent reinforcement learning. Currently, he is mainly involved in the development of algorithms to solve economic situations by employing game theory tools, such as the bargaining problem and the pricing problem; and in the development of a multiagent planner for applications of home automation in biomedical contexts.