5 resultados para Learning and fatigue behavior
em Universitat de Girona, Spain
Resumo:
The main objective of this ex post facto study is to compare the differences in cognitive functions and their relation to schizotypal personality traits between a group of unaffected parents of schizophrenic patients and a control group. A total of 52 unaffected biological parents of schizophrenic patients and 52 unaffected parents of unaffected subjects were assessed in measures of attention (Continuous Performance Test- Identical Pairs Version, CPT-IP), memory and verbal learning (California Verbal Learning Test, CVLT) as well as schizotypal personality traits (Oxford-Liverpool Inventory of Feelings and Experiences, O-LIFE). The parents of the patients with schizophrenia differ from the parents of the control group in omission errors on the Continuous Performance Test- Identical Pairs, on a measure of recall and on two contrast measures of the California Verbal Learning Test. The associations between neuropsychological variables and schizotpyal traits are of a low magnitude. There is no defined pattern of the relationship between cognitive measures and schizotypal traits
Resumo:
In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems
Resumo:
En esta investigación se trata de vincular la autogestión del aprendizaje con el desarrollo de la autonomía personal, la cual favorece el aprendizaje a lo largo de la vida. Partimos, en este proyecto de investigación, de la hipótesis de que la autogestión del aprendizaje es un elemento multidimensional cuya mejora revierte de forma positiva en el desarrollo de la autonomía e iniciativa personal. En esta comunicación se presentan los resultados obtenidos en la aplicación de la fase piloto de un proyecto más amplio, en el que se ha recogido información a través de autoinforme sobre las distintas estrategias y aspectos de la autogestión del aprendizaje y sobre la autonomía e iniciativa personal. Los resultados indican que, en general, hay una relación significativa positiva moderada entre las estrategias de aprendizaje y la autonomía, lo que confirma la importancia de ambos aspectos para favorecer el desarrollo integral de los estudiantes. El fomento de las estrategias de aprendizaje hace que los estudiantes desarrollen la autonomía. A su vez, exponer a los estudiantes a situaciones de aprendizaje que fomenten su autonomía mejora su competencia para aprender
Resumo:
Es desenvolupa una eina de disseny per l'anàlisi de la tolerància al dany en composites. L'eina pot predir el inici i la propagació de fisures interlaminars. També pot ser utilitzada per avaluar i planificar la necessitat de reparar o reemplaçar components durant la seva vida útil. El model desenvolupat pot ser utilitzat tan per simular càrregues estàtiques com de fatiga. El model proposat és un model de dany termodinàmicament consistent que permet simular la delaminació en composites sota càrregues variables. El model es formula dins el context de la Mecànica del Dany, fent ús dels models de zona cohesiva. Es presenta un metodologia per determinar els paràmetres del model constitutiu que permet utilitzar malles d'elements finits més bastes de les que es poden usar típicament. Finalment, el model és també capaç de simular la delaminació produïda per càrregues de fatiga.
Resumo:
This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs