957 resultados para Deep Learning


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Electricity markets are complex environments comprising several negotiation mechanisms. MASCEM (Multi- Agent System for Competitive Electricity Markets) is a simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. ALBidS (Adaptive Learning Strategic Bidding System) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This paper aims to complement ALBidS strategies usage by MASCEM players, providing, through the Six Thinking Hats group decision technique, a means to combine them and take advantages from their different perspectives. The combination of the different proposals resulting from ALBidS’ strategies is performed through the application of a Genetic Algorithm, resulting in an evolutionary learning approach.

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Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

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This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

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The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.

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This chapter appears in Encyclopaedia of Human Resources Information Systems: Challenges in e-HRM edited by Torres-Coronas, T. and Arias-Oliva, M. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL:http://www.igi-pub.com/reference/details.asp?id=7737

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This chapter appears in Encyclopaedia of Distance Learning 2nd Edition edit by Rogers, P.; Berg, Gary; Boettecher, Judith V.; Howard, Caroline; Justice, Lorraine; Schenk, Karen D.. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL: http://www.igi-global.com/reference/ details.asp?ID=9703&v=tableOfContents

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The process of Competences Recognition, Validation and Certification , also known as Accreditation of Prior Learning (APL), is an innovative means of attaining school certificates for individuals without an academic background. The main objective of this process is to validate what people have learned in informal contexts, in order to attribute academic certificates. With the increasing interest of the qualification of workers and governmental support, more and more Portuguese organizations promote this process within their facilities and their work hours. This study explores the relationship between the promotion of this Human Resource Development Programme and employee’s attitudes (Job Satisfaction and Organizational Commitment) and behaviours (Extra-role Organizational Citizenship Behaviours) towards the organization they work for. Results of a cross-sectional survey of Portuguese Industrial Workers (N=135) showed that statistical significant results are in the higher levels of Voice Behaviours (a dimension of Extra-role Organizational Citizenship Behaviour in the groups of workers who were involved or had graduated from the firm promoted APL process.

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Identity achievement is related to personality, as well as cognitive and interpersonal development. In tandem with the deep structural changes that have taken place in society, education must also shift towards a teaching approach focused on learning and the overall development of the student. The integration of technology may be the drive to foster the needed changes. We draw on the literature of multiple subject areas as basis for our work, namely: identity construction and self-representation, within a psychological and social standpoint; Higher Education (HE) in Portugal after Bologna, college student development and other intrinsic relationships, namely the role of emotions and interpersonal relationships in the learning process; the technological evolution of storytelling towards Digital Storytelling (DS) – the Californian model – and its connections to identity and education. Ultimately we propose DS as the aggregator capable of humanizing HE while developing essential skills and competences. Grounded on an interpretative/constructivist paradigm, we implemented a qualitative case study to explore DS in HE. In three attempts to collect student data, we gathered detailed observation notes from two Story Circles; twelve student written reflections; fourteen Digital Stories and detailed observation notes from one Story Show. We carried out three focus groups with teachers where we discussed their perceptions of each student prior to and after watching the Digital Stories, in addition to their opinion on DS in HE as a teaching and learning method and its influence on interpersonal relationships. We sought understandings of the integration of DS to analyze student selfperception and self-representation in HE contexts and intersected our findings with teachers’ perceptions of their students. We compared teachers’ and students’ perspectives, through the analysis of data collected throughout the DS process – Story Circle, Story Creation and Story Show – and triangulated that information with the students’ personal reflections and teacher perceptions. Finally we questioned if and how DS may influence teachers’ perceptions of students. We found participants to be the ultimate gatekeepers in our study. Very few students and teachers voluntarily came forth to take part in the study, confirming the challenge remains in getting participants to see the value and understand the academic rigor of DS. Despite this reluctance, DS proved to be an asset for teachers and students directly and indirectly involved in the study. DS challenges HE contexts, namely teacher established perception of students; student’s own expectations regarding learning in HE; the emotional realm, the private vs. public dichotomy and the shift in educational roles.

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Chapter in Merrill, Barbara (ed.) (2009) Learning to Change? The Role of Identity and Learning Careers in Adult Education. Hamburg: Peter Lang Publishers. URL: http://www.peterlang.com/ index.cfm?vID=58279&vLang=E&vHR=1&vUR=2&vUUR=1

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

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ISCAP’s Information Systems Department is composed of about twenty teachers who have, for several years, been using an e-learning environment (Moodle) combined with traditional assessment. A new e-assessment strategy was implemented recently in order to evaluate a practical topic, the use of spreadsheets to solve management problems. This topic is common to several courses of different undergraduate degree programs. Being e-assessment an outstanding task regarding theoretical topics, it becomes even more challenging when the topics under evaluation are practical. In order to understand the implications of this new type of assessment from the viewpoint of the students, questionnaires and interviews were undertaken. In this paper the analysis of the questionnaires are presented and discussed.

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Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão de Sistemas e-Learning