Learning of shared attention in sociable robotics

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.

Haciendo hologramas en la escuela y en la casa

La comunidad científica que se ocupa de los problemas relacionados con el proceso de enseñanza-aprendizaje de la físicas, ha dedicado muchos esfuerzos en los ultimos años al perfeccionamiento del mismo, motivado en primera instancia, por las demandas de renovación que el impetuoso desarrollo científico-técnico le impone en la actualidad a la enseñanza de las ciencias. En los últimos años se ha producido un desarrollo vertiginoso en la fabricación de diodos láser que emiten en el espectro visible, esto ha permitido su utilización creciente en múltiples aplicaciones y hace factible su utilización en la enseñanza aprendizaje de la física universitaria y en particular de la holografía, por sus grandes ventajas frente a los láseres convencionales de gran costo y difícil manipulación. En el trabajo se describen la instalación experimental portátil diseñada para la obtención de hologramas en la escuela y en la casa con la utilización de diodos láser, la metodología de trabajo a seguir, los métodos de procesamiento utilizados para diferentes tipos de emulsiones holográficas y un análisis de los defectos que pueden presentar los hologramas producidos y la forma de detectarlos y erradicarlos

Proposal for the teaching of the chemical control of supragingival biofilm

The mechanical control of supragingival biofilm is accepted as one of the most important measures to treat and prevent dental caries and periodontal diseases. Nevertheless, maintaining dental surfaces biofilm-free is not an easy task. In this regard, chemical agents, mainly in the form of mouthwashes, have been studied to help overcome the difficulties involved in the mechanical control of biofilm. The aim of this paper was to discuss proposals for the teaching of supragingival chemical control (SCC) in order to improve dentists' knowledge regarding this clinical issue. Firstly, the literature regarding the efficacy of antiseptics is presented, clearly showing that chemical agents are clinically effective in the reduction of biofilm and gingival inflammation when used as adjuvant agents to mechanical control. Thus, it is suggested that the content related to SCC be included in the curricular grid of dental schools. Secondly, some essential topics are recommended to be included in the teaching of SCC as follows: skills and competencies expected of a graduate dentist regarding SCC; how to include this content in the curricular grid; teaching-learning tools and techniques to be employed; and program content.

Cross-situational and supervised learning in the emergence of communication

Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.

Biologically Plausible Connectionist Prediction of Natural Language Thematic Relations

In Natural Language Processing (NLP) symbolic systems, several linguistic phenomena, for instance, the thematic role relationships between sentence constituents, such as AGENT, PATIENT, and LOCATION, can be accounted for by the employment of a rule-based grammar. Another approach to NLP concerns the use of the connectionist model, which has the benefits of learning, generalization and fault tolerance, among others. A third option merges the two previous approaches into a hybrid one: a symbolic thematic theory is used to supply the connectionist network with initial knowledge. Inspired on neuroscience, it is proposed a symbolic-connectionist hybrid system called BIO theta PRED (BIOlogically plausible thematic (theta) symbolic-connectionist PREDictor), designed to reveal the thematic grid assigned to a sentence. Its connectionist architecture comprises, as input, a featural representation of the words (based on the verb/noun WordNet classification and on the classical semantic microfeature representation), and, as output, the thematic grid assigned to the sentence. BIO theta PRED is designed to ""predict"" thematic (semantic) roles assigned to words in a sentence context, employing biologically inspired training algorithm and architecture, and adopting a psycholinguistic view of thematic theory.

Effect of bandwidth knowledge of results on the learning of a grip force control task

An experiment was conducted to investigate the persistence of the effect of ""bandwidth knowledge of results (KR)"" manipulated during the learning phase of performing a manual force-control task. The experiment consisted of two phases, an acquisition phase with the goal of maintaining 60% maximum force in 30 trials, and a second phase with the objective of maintaining 40% of maximum force in 20 further trials. There were four bandwidths of KR: when performance error exceeded 5, 10, or 15% of the target, and a control group (0% bandwidth). Analysis showed that 5, 10, and 15% bandwidth led to better performance than 0% bandwidth KR at the beginning of the second phase and persisted during the extended trials.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

Corporate Education and the Role of the Chief Learning Officer

This paper aims to present an overview on characteristics, roles and responsibilities of those who arc in charge. of the Corporate Educational Systems in several organizations from distinct industries in Brazil, based on a research carried out by the authors. The analysis compares what is available in the literature on this subject so that it may provide insights on how Brazilian companies have dealt with the difficult task of developing competences in their employees. Special attention is given to the Chief Learning Officer`s role (or the lack of it) - someone who was supposed to be in charge of the employees` development processes in a given organization. The results show that this role has not been a clear or unanimous concept yet, neither in terms of the functions to be performed nor the so-called strategic importance given to this sort of executive. This research is both exploratory and descriptive, and due to the use of intentional sample, the inferences are limited. Despite these limitations, its comments may enrich the discussion on this subject.

The teaching of History meets its past: memories of teaching staff during the civil-military dictatorship

The civil-military dictatorship, which took power in 1964, influenced the daily activities of schools and teachers. Many transformations occurred during this period, including the new legislation enacted under Law 5692/71 and changes which occurred due to the vigilance which teachers felt when working. The memories analyzed here of teachers from public schools in Sao Paulo show different perceptions of this surveillance, involving various forms of acceptance or resistance. The purpose of this article is to show that although there was no direct repression of schools, unlike in the universities, teachers at the elementary school also felt constrained and this can be seen in their educational practices and teaching concepts.

Balancing the role of the dental school in teaching, research and patient care; including care for underserved areas

Inequalities within dentistry are common and are reflected in wide differences in the levels of oral health and the standard of care available both within and between countries and communities. Furthermore there are patients, particularly those with special treatment needs, who do not have the same access to dental services as the general public. The dental school should aim to recruit students from varied backgrounds into all areas covered by the oral healthcare team and to train students to treat the full spectrum of patients including those with special needs. It is essential, however, that the dental student achieves a high standard of clinical competence and this cannot be gained by treating only those patients with low expectations for care. Balancing these aspects of clinical education is difficult. Research is an important stimulus to better teaching and better clinical care. It is recognized that dental school staff should be active in research, teaching, clinical work and frequently administration. Maintaining a balance between the commitments to clinical care, teaching and research while also taking account of underserved areas in each of these categories is a difficult challenge but one that has to be met to a high degree in a successful, modern dental school.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.