890 resultados para Distributed artificial intelligence - multiagent systems
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The time division multiple access (TDMA) based channel access mechanisms perform better than the contention based channel access mechanisms, in terms of channel utilization, reliability and power consumption, specially for high data rate applications in wireless sensor networks (WSNs). Most of the existing distributed TDMA scheduling techniques can be classified as either static or dynamic. The primary purpose of static TDMA scheduling algorithms is to improve the channel utilization by generating a schedule of smaller length. But, they usually take longer time to schedule, and hence, are not suitable for WSNs, in which the network topology changes dynamically. On the other hand, dynamic TDMA scheduling algorithms generate a schedule quickly, but they are not efficient in terms of generated schedule length. In this paper, we propose a novel scheme for TDMA scheduling in WSNs, which can generate a compact schedule similar to static scheduling algorithms, while its runtime performance can be matched with those of dynamic scheduling algorithms. Furthermore, the proposed distributed TDMA scheduling algorithm has the capability to trade-off schedule length with the time required to generate the schedule. This would allow the developers of WSNs, to tune the performance, as per the requirement of prevalent WSN applications, and the requirement to perform re-scheduling. Finally, the proposed TDMA scheduling is fault-tolerant to packet loss due to erroneous wireless channel. The algorithm has been simulated using the Castalia simulator to compare its performance with those of others in terms of generated schedule length and the time required to generate the TDMA schedule. Simulation results show that the proposed algorithm generates a compact schedule in a very less time.
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This paper describes the development and evolution of research themes in the Design Theory and Methodology (DTM) conference. Essays containing reflections on the history of DTM, supported by an analysis of session titles and papers winning the ``best paper award'', describe the development of the research themes. A second set of essays describes the evolution of several key research themes. Two broad trends in research themes are evident, with a third one emerging. The topics of the papers in the first decade or so reflect an underlying aim to apply artificial intelligence toward developing systems that could `design'. To do so required understanding how human designers behave, formalizing design processes so that they could be computed, and formalizing representations of design knowledge. The themes in the first DTM conference and the recollections of the DTM founders reflect this underlying aim. The second decade of DTM saw the emergence of product development as an underlying concern and included a growth in a systems view of design. More recently, there appears to be a trend toward design-led innovation, which entails both executing the design process more efficiently and understanding the characteristics of market-leading designs so as to produce engineered products and systems of exceptional levels of quality and customer satisfaction.
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Faz reflexões sobre as várias formas de relação entre sujeitos e objetos-técnicos, com ênfase para a utilização dos computadores digitais e, particularmente, os softwares chamados agentes inteligentes. Analisa o espaço e suas mudanças qualitativas na atualidade, a partir do conceito do espaço como produção humana, analisando como as transformações em curso no ambiente afetam nossas subjetividades e, reciprocamente, como afetamos nossos ambientes. Discutidas as possibilidades de sobrevivência do homem nu nesses novos espaços, sem que esteja devidamente atualizado com as últimas novidades tecnológicas - próteses sensoriais e motoras. Perpassa a discussão sobre o pensamento que se utiliza do espaço como elemento constituinte do próprio pensamento e reflete sobre o espaço abstrato por excelência, os mundos virtuais. Discute o padrão de apropriação de artefatos pelo homem e seus efeitos na subjetividade, a manutenção do padrão de apropriação dos objetos-técnicos materiais em relação às formas de apropriação dos objetos-técnicos intangíveis (softwares). Traz reflexões sobre a possibilidade de autonomização completa dos agentes inteligentes e a sua instituição, ipso facto, como agentes - a chamada Inteligência Artificial.
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Sistemas Multiagentes estão recebendo cada vez mais a atenção de pesquisadores e desenvolvedores de jogos virtuais. O uso de agentes permite controlar o desempenho do usuário, adaptando a interface e alterando automaticamente o nível de dificuldade das tarefas. Este trabalho descreve uma estratégia de integração de sistemas multiagentes e ambientes virtuais tridimensionais e exemplifica a viabilidade dessa integração através do desenvolvimento de um jogo com características de Serious game. Este jogo visa estimular as funções cognitivas, tais como atenção e memória e é voltado para pessoas portadoras de diferentes distúrbios neuropsiquiátricos. A construção do jogo foi apoiada em um processo de desenvolvimento composto por várias etapas: estudos teóricos sobre as áreas envolvidas, estudo de tecnologias capazes de apoiar essa integração, levantamento de requisitos com especialistas, implementação e avaliação com especialistas. O produto final foi avaliado por especialistas da área médica, que consideraram os resultados como positivos.
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Although partially observable Markov decision processes (POMDPs) have shown great promise as a framework for dialog management in spoken dialog systems, important scalability issues remain. This paper tackles the problem of scaling slot-filling POMDP-based dialog managers to many slots with a novel technique called composite point-based value iteration (CSPBVI). CSPBVI creates a "local" POMDP policy for each slot; at runtime, each slot nominates an action and a heuristic chooses which action to take. Experiments in dialog simulation show that CSPBVI successfully scales POMDP-based dialog managers without compromising performance gains over baseline techniques and preserving robustness to errors in user model estimation. Copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.
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Holistic representations of natural scenes is an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequency domain has been successfully exploited to holistically encode the content of natural scenes in order to obtain a robust representation for scene classification. In this paper, we present a new approach to naturalness classification of scenes using frequency domain. The proposed method is based on the ordering of the Discrete Fourier Power Spectra. Features extracted from this ordering are shown sufficient to build a robust holistic representation for Natural vs. Artificial scene classification. Experiments show that the proposed frequency domain method matches the accuracy of other state-of-the-art solutions. © 2008 Springer Berlin Heidelberg.
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This paper presents an overview of the Text-to-Speech synthesis system developed at the Institute for Language and Speech Processing (ILSP). It focuses on the key issues regarding the design of the system components. The system currently fully supports three languages (Greek, English, Bulgarian) and is designed in such a way to be as language and speaker independent as possible. Also, experimental results are presented which show that the system produces high quality synthetic speech in terms of naturalness and intelligibility. The system was recently ranked among the first three systems worldwide in terms of achieved quality for the English language, at the international Blizzard Challenge 2013 workshop. © 2014 Springer International Publishing.
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The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program - a set of algorithms to process symbols - has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face. © Springer-Verlag Berlin Heidelberg 2007.