156 research outputs found
Characterization Results for the Poset Based Representation of Topological Relations - II: Intersection and Union
No full text@article{DBLP:journals/informaticaSI/ForlizziN00,
author = {Luca Forlizzi and
Enrico Nardelli},
title = {Characterization Results for the Poset Based Representation
of Topological Relations - II: Intersection and Union.},
journal = {Informatica (Slovenia)},
volume = {24},
number = {1},
year = {2000},
bibsource = {DBLP, http://dblp.uni-trier.de}
Characterization Results for the Poset Based Representation of Topological Relations - I: Introduction and Models
No full text@article{DBLP:journals/informaticaSI/ForlizziN99,
author = {Luca Forlizzi and
Enrico Nardelli},
title = {Characterization Results for the Poset Based Representation
of Topological Relations - I: Introduction and Models.},
journal = {Informatica (Slovenia)},
volume = {23},
number = {2},
year = {1999},
bibsource = {DBLP, http://dblp.uni-trier.de}
Algorithms for Moving Objects Databases
No full text@article{DBLP:journals/cj/LemaFGNS03,
author = {Jos{'e} Antonio Cotelo Lema and
Luca Forlizzi and
Ralf Hartmut G{"u}ting and
Enrico Nardelli and
Markus Schneider},
title = {Algorithms for Moving Objects Databases.},
journal = {Comput. J.},
volume = {46},
number = {6},
year = {2003},
pages = {680-712},
ee = {http://www3.oup.co.uk/computer_journal/current/460680.sgm.abs.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
Imparare ad imparare: Decostruire una storia per costruire la nostra storia
No full textDescriviamo una esperienza di avvio al pensiero computazionale attraverso attività di programmazione in ambiente Scratch realizzata in una classe seconda di scuola secondaria di I grado con insegnanti che stavano frequentando un corso di aggiornamento delle loro competenze digitali. Obiettivo di questa specifica esperienza è stato abituare alunni ed insegnanti ad imparare, da quello che già funziona, come risolvere i problemi che sorgono nella realizzazione di un nuovo progetto. Il modus operandi è decostruire una attività, nel caso in questione un programma realizzato in Scratch, andando ad individuare la soluzione ad un problema di interesse, astrarre questa soluzione e poi specializzarla a quanto interessa a noi realizzare. Così facendo ci uniamo a Dewey nel “...far conquistare agli allievi la pratica di scoprire come risolvere un problema da soli” [5] esercitando una forma dell’imparare ad imparare.
Si evidenzia come l’uso dell’ambiente Scratch faciliti l’individuazione, in particolare la verifica, della componente che in una attività funzionante può essere utile per una attività in costruzione.We describe an experience introducing computational thinking through programming using the Scratch environment. The activity has been carried out in a second grade middle school class with teachers who were undergoing a course for upgrading their digital skills. The objective of this specific experience was to get both students and teachers to learn how to solve the problems that arise in the implementation of a new project from programming activities already working. The modus operandi is to deconstruct an activity, in our case a Scratch program, in order to find in it the solution to a problem, then abstracting this solution and finally specializing again the abstraction into what interests us to have in the new project. By doing so, we join Dewey in "... making students learn the practice of finding out how to solve a problem on their own" [5] by exercising a form of learning to learn. We point out how using the Scratch environment facilitates the identification of the component that, in an already running activity, can be useful for another activity under implementation. In particular the Scratch environment simplifies verifying that the component works in the new context
A multi-touch interface for multi-robot path planning and control
No full textIn the last few years, research in human-robot interaction has moved beyond the issues concerning the design of the interaction between a person and a single robot. Today many researchers have shifted their focus toward the problem of how humans can control a multi-robot team. The rising of multi-touch devices provides a new range of opportunities in this sense. Our research seeks to discover new insights and guidelines for the design of multi-touch interfaces for the control of biologically inspired multi-robot teams. We have developed an iPad touch interface that lets users exert partial control over a set of autonomous robots. The interface also serves as an experimental platform to study how human operators design multi-robot motion in a pursuit-evasion setting
On the Inapproximability of Finding Minimum Monitoring Edge-Geodetic Sets (short paper)
No full textGiven an undirected connected graph G = (V(G), E(G)) on n vertices, the minimum Monitoring Edge-Geodetic Set (MEG-set) problem asks to find a subset M subset of V(G) of minimum cardinality such that, for every edge e in E(G), there exist x, y in M for which all shortest paths between x and y in G traverse e. We show that, for any constant c < 1/2, no polynomial-time (c log n)-approximation algorithm for the minimum MEG-set problem exists, unless P = NP
An algorithm composition scheme preserving monotonicity
No full textLet G=(V,E) be a graph modeling a network where each edge is owned by a selfish agent, which establishes the cost for using her edge by pursuing only her personal utility. In such a setting, several classic network optimization problems, like for instance many graph traversal problems, asks for solutions in which an edge of G can be used several times. In game-theoretic terms, these problems are known as one-parameter problems, but with a peculiarity: the workload of each agent is a natural number. In this paper we refine the classic notion of monotonicity of an algorithm so as to exactly capture this property, and we then provide a general technique to efficiently develop truthful mechanisms for this family of problems
Approximate Mechanisms for the Graphical TSP and Other Graph-Traversal Problems
No full textLet G = (V,E) be a graph modeling a network in which each edge is owned by a selfish agent, which establishes the cost for traversing its edge (i.e., assigns a weight to its edge) by pursuing only its personal utility. In such a setting, we aim at designing approximate truthful mechanisms for several NP-hard traversal problems on G, such as the graphical traveling salesman problem, the rural postman problem, and the mixed Chinese postman problem, each of which in general requires an edge of G to be used several times. Thus, in game-theoretic terms, these are one-parameter problems, but with a peculiarity: the workload of each agent is a natural number. In this paper we refine the classical notion of monotonicity of an algorithm so as to capture exactly this property, and we then provide a general mechanism-design technique that guarantees this monotonicity and that allows one to compute efficiently the corresponding payments. In this way, we show that the former two problems and the latter one admit a 3/2-and a 2-approximate truthful mechanism, respectively. Thus, for the first two problems we match the best known approximation ratios holding for their corresponding centralized versions, while for the third one we are only a 4/3-factor away from it
Approximate Mechanisms for the Metric TSP and other Graph Traversal Problems
No full textLet G = (V,E) be a graph modeling a network in which each edge is
owned by a selfish agent, which establishes the cost for traversing its edge (i.e., assigns
a weight to its edge) by pursuing only its personal utility. In such a setting, we aim
at designing approximate truthful mechanisms for several NP-hard traversal problems
on G, such as the graphical traveling salesman problem, the rural postman problem,
and the mixed Chinese postman problem, each of which in general requires an edge of
G to be used several times. Thus, in game-theoretic terms, these are one-parameter
problems, but with a peculiarity: the workload of each agent is a natural number.
In this paper we refine the classical notion of monotonicity of an algorithm so as
to capture exactly this property, and we then provide a general mechanism-design
technique that guarantees this monotonicity and that allows one to compute efficiently
the corresponding payments. In this way, we show that the former two problems and the
latter one admit a 3/2- and a 2-approximate truthful mechanism, respectively. Thus,
for the first two problems we match the best known approximation ratios holding for
their corresponding centralized versions, while for the third one we are only a 4/3-factor
away from it
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