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ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal    [5 followers]  Follow    
  This is an Open Access Journal Open Access journal
     ISSN (Print) 2255-2863
     Published by Universidad de Salamanca Homepage  [2 journals]
  • An Integrated System for Disabled People Developed with the Agent Platform
           PANGEA
    • Authors: Carolina ZATO, Gabriel VILLARRUBIA, Javier BAJO, Juan Manuel CORCHADO
      Abstract: New trends in multi-agent systems call for self-adaptation and high dynamics, hence the new model of open MAS or virtual organization of agents. However, as existing agent platforms are not yet equipped to support this behavior, it is necessary to create new systems and mechanisms to facilitate the development of these new architectures. This article presents PANGEA, an agent platform to develop open multi-agent systems, specifically those including organizational aspects such as virtual agent organizations. The platform allows the integral management of organizations and offers tools to the end user. Additionally, it includes a communication protocol based on the IRC standard, which facilitates implementation and remains robust even with a large number of connections. The introduction of a CommunicationAgent and a Sniffer make it possible to offer Web Services for the distributed control of interaction. In order to test PANGEA, an integral system was developed to help the disabled, gathering a set of easily deployable and integrated services under a single architecture.
      PubDate: 2013-11-27
      Issue No: Vol. 1 (2013)
       
  • MDD-Approach for developing Pervasive Systems based on Service-Oriented
           Multi-Agent Systems
    • Authors: Jorge AGÜERO, Miguel REBOLLO, Carlos CARRASCOSA, Vicente JULIÁN
      Abstract: The development of Ubiquitous or Pervasive Systems can be considered a complex task, with multiple actors, devices and different hardware environments; where it is difficult to find a compact view of all the components. This work proposes to use a MDD (Model-Driven Development) approach to facilitate the development process of Agent-Based Pervasive Systems, providing the user with a set of abstractions that ease the implementation of Pervasive Systems and the deployment of a platform for their execution. The proposal allows designing pervasive applications using high-level abstractions, avoiding the low-level implementation details and, after that, the Pervasive System deployment (with embedded agents and devices) is generated by using automatic transformations. In this way, a non-expert programmer will be able to develop Agent-Based Pervasive Systems, reducing the gap between the design and the implementation phases.
      PubDate: 2013-11-25
      Issue No: Vol. 1 (2013)
       
  • A multi-agent architecture to combine heterogeneous inputs in multimodal
           interaction systems
    • Authors: David GRIOL, Jesús GARCÍA-HERRERO, José Manuel MOLINA
      Abstract: In this paper we present a multi-agent architecture for the integration of visual sensor networks and speech-based interfaces. The proposed architecture combines different techniques related to Artificial Intelligence, Natural Language Processing and User Modeling to provide an enhanced interaction with their users. Firstly, the architecture integrates a Cooperative Surveillance Multi-Agent System (CS-MAS), which includes several types of autonomous agents working in a coalition to track and make inferences on the positions of the targets. Secondly, the proposed architecture incorporates enhanced conversational agents to facilitate human-computer interaction by means of speech interaction. Thirdly, a statistical methodology allows to model the user conversational behavior, which is learned from an initial corpus and posteriorly improved with the knowledge acquired from the successive interactions. A technique is proposed to facilitate the multimodal fusion of these information sources and consider the result for the decision of the next system action.
      PubDate: 2013-11-25
      Issue No: Vol. 1 (2013)
       
  • Irrigation System through Intelligent Agents Implemented with Arduino
           Technology
    • Authors: Rodolfo SALAZAR, José Carlos RANGEL, Cristian PINZÓN, Abel RODRÍGUEZ
      Abstract: The water has become in recent years a valuable and increasingly scarce. Its proper use in agriculture has demanded incorporate new technologies, mainly in the area of ICT. In this paper we present a smart irrigation system based on multi-agent architecture using fuzzy logic. The architecture incorporates different types of intelligent agents that an autonomous way monitor and are responsible for deciding if required enable / disable the irrigation system. This project proposes a real and innovative solution to the problem of inadequate water use with current irrigation systems employed in agricultural projects. This article presents the different technologies used, their adaptation to the solution of the problem and briefly discusses the first results obtained.
      PubDate: 2013-11-25
      Issue No: Vol. 1 (2013)
       
  • Designing a Web Spam Classifier Based on Feature Fusion in the Layered
           Multi-Population Genetic Programming Framework
    • Authors: Amir Hosein KEYHANIPOUR, Behzad MOSHIRI
      Abstract: Nowadays, Web spam pages are a critical challenge for Web retrieval systems which have drastic influence on the performance of such systems. Although these systems try to combat the impact of spam pages on their final results list, spammers increasingly use more sophisticated techniques to increase the number of views for their intended pages in order to have more commercial success. This paper employs the recently proposed Layered Multi-population Genetic Programming model for Web spam detection task as well application of correlation coefficient analysis for feature space reduction. Based on our tentative results, the designed classifier, which is based on a combination of easy to compute features, has a very reasonable performance in comparison with similar methods.
      PubDate: 2013-11-25
      Issue No: Vol. 1 (2013)
       
  • Machine Learning ANN Models for Predicting Sensory Quality of Roasted
           Coffee Falvoured Sterilized Drink
    • Authors: Sumit GOYAL, Gyanendra Kumar GOYAL
      Abstract: This paper highlights the significance of feedforward artificial neural network models for predicting shelf life of roasted coffee falvoured sterilized drink. Coffee is one of the most important products for trade in international market. Single as well as multilayer models were explored and different backpropagation algorithms were investigated, Root mean square error and coefficient of determination R2 were used to compare the prediction performance of single and multilayer feedforward ANN models. Experimental results suggested that multilayer models take less time and give better results as compared to single layer ANN models for prediction of sensory quality of roasted coffee falvoured sterilized drink..
      PubDate: 2013-11-25
      Issue No: Vol. 1 (2013)
       
  • Inference in Belief Network using Logic Sampling and Likelihood Weighing
           algorithms
    • Authors: K. S. JASMINE, Gavani PRATHVIRAJ S., P Ijantakar RAJASHEKAR, K. A. SUMITHRA DEVI
      Abstract: Over the time in computational history, belief networks have become an increasingly popular mechanism for dealing with uncertainty in systems. It is known that identifying the probability values of belief network nodes given a set of evidence is not amenable in general. Many different simulation algorithms for approximating solution to this problem have been proposed and implemented. This paper details the implementation of such algorithms, in particular the two algorithms of the belief networks namely Logic sampling and the likelihood weighing are discussed. A detailed description of the algorithm is given with observed results. These algorithms play crucial roles in dynamic decision making in any situation of uncertainty.
      PubDate: 2013-11-25
      Issue No: Vol. 1 (2013)
       
 
 
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