319,062 research outputs found
Dimensions of Neural-symbolic Integration - A Structured Survey
Research on integrated neural-symbolic systems has made significant progress
in the recent past. In particular the understanding of ways to deal with
symbolic knowledge within connectionist systems (also called artificial neural
networks) has reached a critical mass which enables the community to strive for
applicable implementations and use cases. Recent work has covered a great
variety of logics used in artificial intelligence and provides a multitude of
techniques for dealing with them within the context of artificial neural
networks. We present a comprehensive survey of the field of neural-symbolic
integration, including a new classification of system according to their
architectures and abilities.Comment: 28 page
Properties of ABA+ for Non-Monotonic Reasoning
We investigate properties of ABA+, a formalism that extends the well studied
structured argumentation formalism Assumption-Based Argumentation (ABA) with a
preference handling mechanism. In particular, we establish desirable properties
that ABA+ semantics exhibit. These pave way to the satisfaction by ABA+ of some
(arguably) desirable principles of preference handling in argumentation and
nonmonotonic reasoning, as well as non-monotonic inference properties of ABA+
under various semantics.Comment: This is a revised version of the paper presented at the worksho
Relating emotional intelligence to academic achievement among university students in Barbados
This study investigated the relationships between emotional intelligence and academic
achievement among 151 undergraduate psychology students at The University of the
West Indies (UWI), Barbados, making use of Barchard (2001)’s Emotional Intelligence
Scale and an Academic Achievement Scale. Findings revealed significant positive
correlations between academic achievement and six of the emotional intelligence
components, and a negative correlation with negative expressivity. The emotional
intelligence components also jointly contributed 48% of the variance in academic
achievement. Attending to emotions was the best predictor of academic achievement
while positive expressivity, negative expressivity and empathic concern were other
significant predictors. Emotion-based decision-making, responsive joy and responsive
distress did not make any significant relative contribution to academic achievement,
indicating that academic achievement is only partially predicted by emotional
intelligence. These results were discussed in the context of the influence of emotional
intelligence on university students’ academic achievement.peer-reviewe
A Tutorial on Bayesian Nonparametric Models
A key problem in statistical modeling is model selection, how to choose a
model at an appropriate level of complexity. This problem appears in many
settings, most prominently in choosing the number ofclusters in mixture models
or the number of factors in factor analysis. In this tutorial we describe
Bayesian nonparametric methods, a class of methods that side-steps this issue
by allowing the data to determine the complexity of the model. This tutorial is
a high-level introduction to Bayesian nonparametric methods and contains
several examples of their application.Comment: 28 pages, 8 figure
Inter-individual cognitive variability in children with Asperger's syndrome
Multiple studies have tried to establish the distinctive profile of individuals with Asperger's syndrome (AS). However, recent reports suggest that adults with AS feature heterogeneous cognitive profiles. The present study explores inter-individual variability in children with AS through group comparison and multiple case series analysis. All participants completed an extended battery including measures of fluid and crystallized intelligence, executive functions, theory of mind, and classical neuropsychological tests. Significant group differences were found in theory of mind and other domains related to global information processing. However, the AS group showed high inter-individual variability (both sub- and supra-normal performance) on most cognitive tasks. Furthermore, high fluid intelligence correlated with less general cognitive impairment, high cognitive flexibility, and speed of motor processing. In light of these findings, we propose that children with AS are characterized by a distinct, uneven pattern of cognitive strengths and weaknesses.Fil: González Gadea, MarĂa Luz. Universidad Diego Portales; Chile. Universidad Favaloro; Argentina. Instituto de NeurologĂa Cognitiva; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Tripicchio, Paula. Instituto de NeurologĂa Cognitiva; Argentina. Universidad Favaloro; ArgentinaFil: Rattazzi del Carril, Alexia. Instituto de NeurologĂa Cognitiva; Argentina. Universidad Favaloro; ArgentinaFil: Báez Buitrago, Sandra Jimena. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Universidad Catolica Argentina; Argentina. Instituto de NeurologĂa Cognitiva; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Marino, Julián Carlos. Universidad Nacional de CĂłrdoba. Facultad de PsicologĂa; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Roca, MarĂa. Universidad Favaloro; Argentina. Instituto de NeurologĂa Cognitiva; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Manes, Facundo Francisco. Instituto de NeurologĂa Cognitiva; Argentina. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Centre of Excellence in Cognition and its Disorders; AustriaFil: Ibanez Barassi, Agustin Mariano. Instituto de NeurologĂa Cognitiva; Argentina. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Centre of Excellence in Cognition and its Disorders; Austria. Universidad Autonoma del Caribe; Colombi
Fostering collective intelligence education
New educational models are necessary to update learning environments to the digitally shared communication and information. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified.Postprint (published version
A graph-based mathematical morphology reader
This survey paper aims at providing a "literary" anthology of mathematical
morphology on graphs. It describes in the English language many ideas stemming
from a large number of different papers, hence providing a unified view of an
active and diverse field of research
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