978 resultados para Learning behavior
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Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved.
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The intensification of the production system in the poultry industry and the vertical integration of the poultry agribusiness have brought profound changes in the physical and social environment of domestic fowls in comparison to their ancestors and have modified the expression of aggression and submission. The present review has covered the studies focusing on the different aspects linked to aggressiveness in the genus Gallus. The evaluated studies have shown that aggressiveness and subordination are complex behavioral expressions that involve genetic differences between breeds, strains and individuals, and differences in the cerebral development during growth, in the hormonal metabolism, in the rearing conditions of individuals, including feed restriction, density, housing type (litter or cage), influence of the opposite sex during the growth period, existence of hostile stimuli (pain and frustration), ability to recognize individuals and social learning. The utilization of fighting birds as experimental material in the study of mechanisms that have influence on the manifestation of aggressiveness in the genus Gallus might comparatively help to elucidate important biological aspects of such behavior.
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On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the behavior of other agents may change as they simultaneously learn how to improve their actions. Non-stationary scenarios can be modeled as Markov Games, which can be solved using the Minimax-Q algorithm a combination of Q-learning (a Reinforcement Learning (RL) algorithm which directly learns an optimal control policy) and the Minimax algorithm. However, finding optimal control policies using any RL algorithm (Q-learning and Minimax-Q included) can be very time consuming. Trying to improve the learning time of Q-learning, we considered the QS-algorithm. in which a single experience can update more than a single action value by using a spreading function. In this paper, we contribute a Minimax-QS algorithm which combines the Minimax-Q algorithm and the QS-algorithm. We conduct a series of empirical evaluation of the algorithm in a simplified simulator of the soccer domain. We show that even using a very simple domain-dependent spreading function, the performance of the learning algorithm can be improved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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First graders, preschoolers, special education students, and adults received a reading program in which they learned to match printed to dictated words and to construct (copy) printed words. The students not only learned to match the training words but also learned to read them. In addition, most of the students learned to read new words that involved recombinations of the syllables of the training words. The results replicate and extend the generality of a prior analysis of a reading program based on stimulus equivalence and recombination of units.
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Introduction the selective serotonin reuptake inhibitors have become the most frequently prescribed drugs for the treatment of depression. Sexual side effects have been noted to occur with this treatment on heterosexual behavior in rats. Heterosexual experience facilitates sexual orientation of male rats and decreases the latencies to first mount and first intromission. on the other hand, homosexual behavior in male rats induced by female hormones has not been evaluated.Aim the objective of this work is to evaluate the effects of heterosexual and homosexual experience in male rats long-term treated with fluoxetine (FLX) on homosexual hormone-induced behavior.Materials and Methods Male rats were treated with FLX or saline solution (10 mg/kg for 65 days). At days 36, 50, and 65 of the treatment, the rats were evaluated for homosexual behavior. Other rats treated with FLX or saline solution for 60 consecutive days were submitted to heterosexual behavior at 14, 21, and 28 days of the treatment. After this, they were orquiectomized and homosexual hormone-induced behavior was observed at 45 and 60 days of the treatment.Results (1) Only treatment with FLX did not affect the homosexual behavior. (2) the homosexual experience facilitated the homosexual behavior mainly on the animals from the control group. (3) the heterosexual experience facilitated the homosexual behavior on both groups.Conclusions Only long-term administration of FLX does not interfere with the homosexual behavior in male rats. The homosexual and the heterosexual experience facilitated the homosexual behavior on the control and experimental groups. We suggested that learning aspects related to sexual behavior are responsible by these results.
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This four-experiment series sought to evaluate the potential of children with neurosensory deafness and cochlear implants to exhibit auditory-visual and visual-visual stimulus equivalence relations within a matching-to-sample format. Twelve children who became deaf prior to acquiring language (prelingual) and four who became deaf afterwards (postlingual) were studied. All children learned auditory-visual conditional discriminations and nearly all showed emergent equivalence relations. Naming tests, conducted with a subset of the: children, showed no consistent relationship to the equivalence-test outcomes.. This study makes several contributions: to the literature on stimulus equivalence. First; it demonstrates that both pre- and postlingually deaf children-can: acquire auditory-visual equivalence-relations after cochlear implantation, thus demonstrating symbolic functioning. Second, it directs attention to a population that may be especially interesting for researchers seeking to analyze the relationship. between speaker and listener repertoires. Third, it demonstrates the feasibility of conducting experimental studies of stimulus control processes within the limitations of a hospital, which these children must visit routinely for the maintenance of their cochlear implants.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Includes bibliography
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This paper presents novel simulation tools to assist the lecturers about learning processes on renewable energy sources, considering photovoltaic (PV) systems. The PV behavior, functionality and its interaction with power electronic converters are investigated in the simulation tools. The main PV output characteristics, I (current) versus V (voltage) and P (power) versus V (voltage), were implemented in the tools, in order to aid the users for the design steps. In order to verify the effectiveness of the developed tools the simulation results were compared with Matlab. Finally, a prototype was implemented with the purpose to compare the experimental results with the results from the proposed tools, validating its operational feasibility. © 2011 IEEE.
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This paper presents the analysis and evaluation of the Power Electronics course at So Paulo State University-UNESP-Campus of Ilha Solteira(SP)-Brazil, which includes the usage of interactive Java simulations tools and an educational software to aid the teaching of power electronic converters. This platform serves as an oriented course for the lectures and supplementary support for laboratory experiments in the power electronics courses. The simulation tools provide an interactive and dynamic way to visualize the power electronics converters behavior together with the educational software, which contemplates the theory and a list of subjects for circuit simulations. In order to verify the performance and the effectiveness of the proposed interactive educational platform, it is presented a statistical analysis considering the last three years. © 2011 IEEE.
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This paper aims to present the use of a learning object (CADILAG), developed to facilitate understanding data structure operations by using visual presentations and animations. The CADILAG allows visualizing the behavior of algorithms usually discussed during Computer Science and Information System courses. For each data structure it is possible visualizing its content and its operation dynamically. Its use was evaluated an the results are presented. © 2012 AISTI.
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Plant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. Digital cameras have been successfully used as multi-channel imaging sensors, providing measures of leaf color change information (RGB channels), or leafing phenological changes in plants. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract RGB channels from digital images and correlated with phenological changes. Our first goals were: (1) to test if the color change information is able to characterize the phenological pattern of a group of species; and (2) to test if individuals from the same functional group may be automatically identified using digital images. In this paper, we present a machine learning approach to detect phenological patterns in the digital images. Our preliminary results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; and (2) different plant species present a different behavior with respect to the color change information. Based on those results, we suggest that individuals from the same functional group might be identified using digital images, and introduce a new tool to help phenology experts in the species identification and location on-the-ground. ©2012 IEEE.
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Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.
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In this study, we show that the fish Nile tilapia displays an antipredator response to chemical cues present in the blood of conspecifics. This is the first report of alarm response induced by blood-borne chemical cues in fish. There is a body of evidence showing that chemical cues from epidermal 'club' cells elicit an alarm reaction in fish. However, the chemical cues of these 'club' cells are restricted to certain species of fish. Thus, as a parsimonious explanation, we assume that an alarm response to blood cues is a generalized response among animals because it occurs in mammals, birds and protostomian animals. Moreover, our results suggest that researchers must use caution when studying chemically induced alarm reactions because it is difficult to separate club cell cues from traces of blood. © 2013 Barreto et al.