59 research outputs found
A Psychogenetic Algorithm For Behavioral Sequence Learning
No full textThis work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J. Piaget. Specifically, we modeled some elements of cognitive structure learning in children from birth to four months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences
VERY STRONGLY CONSTRAINED PROBLEMS: AN ANT COLONY OPTIMIZATION APPROACH
No full textAnt Colony Optimization (ACO) is a class of metaheuristic algorithms sharing the common approach of constructing a solution on the basis of information provided both by a standard constructive heuristic and by previously constructed solutions. This paper is composed of three parts. The first on
Method,and corresponding apparatus,for automatic detection of regions of interest in digital images of biological tissue
No full textCar Racing through the Streets of the Web: A High Speed 3D Game over a Fast Synchronization Service
No full textUNA TEORIA PSICOGENETICA PER L’APPRENDIMENTO AUTOMATICO DI REGOLE PER IL DATAMINING
No full textPresentiamo uno studio preliminare alla fattibilità dell’utilizzo di una trasposizione algoritmica di alcuni aspetti della teoria psicogenetica a problematiche di datamining. La psicogenetica studia la formazione di strutture cognitive nei bambini, riteniamo che gli stessi meccanismi possano essere criterio ispiratore di algoritmi di apprendimento automatico che portino alla definizione di regole e alberi di classificazione più flessibili di quelli finora proposti in letteratur
Matheuristics in simulation: a case study in water supply management
No full textOptimization and simulation are close relatives, it is thus expected that techniques from the former
can migrate to the latter. In recent years, a trend has been established, that uses techniques
originally conceived for exact optimization as elements for heuristic design. The same idea transfers
to simulation, where there are occasions where exact subroutines applied to specific subproblems
can be of help for determining the forecasted trajectory of some varibles of interest.
This work reports about a real-world application along this line,
where an exact optimization subroutine has been used to simulate the expected behavior of some
variables related to the management of water basins
Support Vector Machines in CAD Mammography
No full textThe chapter will focus on the use of machine learning techniques, such as Support Vector Machines (SVM), in CAD issues. First, an introduction of SVMs will be presented, with a particular attention to their use as classifiers. A brief theory preamble and a survey of advantages of SVMs over other classifiers will be provided. Finally, examples of mass and microcalcifications detection based on SVMs will be described and reviewed. Particular emphasis will be given to detection techniques which do not make use of extracted features for isolating the suspect regions
Matheuristics for Traffic Counter Location
No full textMatheuristic algorithms have begun to demonstrate that they can
be the state of the art for some optimization problems. This paper
puts forth that they can represent a viable option also in an applicative
context. The possibility to get a solution quality validation
or a model grounded construction may become a significant
competitive advantage against alternative approaches. This view
is substantiated in this work by an application on the problem of
determining the best set of locations for a constrained number of
traffic counters, to the end of estimating a traffic origin / destination
matrix. We implemented a Lagrangean heuristic and tested
it on instances of different size. A real world use case is also reported
A participatory framework to support inclusive multi-playing for gamers in disadvantaged conditions
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