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Stefano Troiani

dblp:51/8366 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › multi-robot coordination
multi-robot patrolling
0.112010
Moving game theoretical patrolling strategies from theory to practice: An USARSim simulation · ICRA 2010

Methods — techniques the papers use, named apart from their topics

simulation · 0.1game theory · 0.1
YearPublicationVenuePosition
2010 Moving game theoretical patrolling strategies from theory to practice: An USARSim simulation
abstract
Game theoretical approaches have been recently used to develop patrolling strategies for mobile robots. The idea is that the patroller and the intruder play a game, whose outcome depends on the combination of their actions. From the analysis of this game, an optimal strategy for the patrolling robot can be derived. Although game theoretical approaches are promising, their applicability in real settings is still an open problem. In this paper, we experimentally evaluate the practical applicability of the most general game theoretical approach for patrolling strategies, called BGA model. Experiments are conducted by using USARSim, with the goal of studying the behavior of the optimal patrolling strategy returned by the BGA model both in situations that violate its idealized assumptions and in comparison with other patrolling strategies that can be developed with much less computational effort.
Francesco Amigoni, Nicola Basilico, Nicola Gatti 0001, Alessandro Saporiti, Stefano Troiani
ICRA5