305 research outputs found

    A Concurrent Fuzzy-Neural Network Approach for Decision Support Systems

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    Decision-making is a process of choosing among alternative courses of action for solving complicated problems where multi-criteria objectives are involved. The past few years have witnessed a growing recognition of Soft Computing technologies that underlie the conception, design and utilization of intelligent systems. Several works have been done where engineers and scientists have applied intelligent techniques and heuristics to obtain optimal decisions from imprecise information. In this paper, we present a concurrent fuzzy-neural network approach combining unsupervised and supervised learning techniques to develop the Tactical Air Combat Decision Support System (TACDSS). Experiment results clearly demonstrate the efficiency of the proposed technique

    Future Trends of Virtual, Augmented Reality, and Games for Health

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    Serious game is now a multi-billion dollar industry and is still growing steadily in many sectors. As a major subset of serious games, designing and developing Virtual Reality (VR), Augmented Reality (AR), and serious games or adopting off-the-shelf games to support medical education, rehabilitation, or promote health has become a promising frontier in the healthcare sector since 2004, because games technology is inexpensive, widely available, fun and entertaining for people of all ages, with various health conditions and different sensory, motor, and cognitive capabilities. In this chapter, we provide the reader an overview of the book with a perspective of future trends of VR, AR simulation and serious games for healthcare

    Image inpainting based on self-organizing maps by using multi-agent implementation

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    AbstractThe image inpainting is a well-known task of visual editing. However, the efficiency strongly depends on sizes and textural neighborhood of “missing” area. Various methods of image inpainting exist, among which the Kohonen Self-Organizing Map (SOM) network as a mean of unsupervised learning is widely used. The weaknesses of the Kohonen SOM network such as the necessity for tuning of algorithm parameters and the low computational speed caused the application of multi- agent system with a multi-mapping possibility and a parallel processing by the identical agents. During experiments, it was shown that the preliminary image segmentation and the creation of the SOMs for each type of homogeneous textures provide better results in comparison with the classical SOM application. Also the optimal number of inpainting agents was determined. The quality of inpainting was estimated by several metrics, and good results were obtained in complex images

    Preface

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    THE LINK BETWEEN AGENT COORDINATION AND COOPERATION

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    Abstract: Agent coordination is the ability to manage the interdependencies of activities between agents while agent cooperation is the process used for an agent to voluntarily enter a relationship with another to achieve a system derived goal. We describe and show the concepts of Coordinative Cooperation and Cooperative Coordination using examples. These concepts demonstrate the ability for intelligent agents to distinguish between cooperation from coordination and vice-versa. Both concepts can be integrated into a process, using a cognitive cycle to explain the interaction between coordination and cooperation. Furthermore, this paper will discuss how the coordination/cooperation loop is initialised and can be affected by Coordinative and Cooperative events. We recommend suggestions on how these concepts can be designed and implemented in a multiagent system (MAS) and introduce AC 3 M, which is a prototype of this cognitive loop
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