Holonic multi-agent system model for fuzzy automatic speech / speaker recognition

An automatic speech / speaker recognition (ASSR) system has to adapt to possible changes of speaker and environment conditions, and act as close as possible to the way a human recognizes speeches / speakers. This kind of very complex system has to deal with speech signals, looking for the integration of different information sources; and this is precisely the reason to use fuzzy logic. The main objective of this paper is the description of a robust, intelligent and adaptive system, modeled as a multi-agent system (MAS), forming a recursive hierarchy of MAS denominated holonic MAS

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Prometheus and ingenias agent methodologies: a complementary approach.

A great number of methodologies to develop multi-agent systems (MAS) have been proposed in the last few years. But a unique methodology cannot be general enough to be useful for everyone without some level of customization. According to our knowledge, existent agent-based surveillance systems have been developed ad-hoc and no methodology has been followed. We are interested in creating tools that allow to model and to generate monitoring environments. This has motivated the selection of Prometheus and INGENIAS methodologies, to take advantage of both approaches in developing agent-based applications. In this paper a collection of equivalences between the concepts used in both methodologies is described extensively

Organization based multiagent architecture for distributed environments

[EN]Distributed environments represent a complex field in which applied solutions should be flexible and include significant adaptation capabilities. These environments are related to problems where multiple users and devices may interact, and where simple and local solutions could possibly generate good results, but may not be effective with regards to use and interaction. There are many techniques that can be employed to face this kind of problems, from CORBA to multi-agent systems, passing by web-services and SOA, among others. All those methodologies have their advantages and disadvantages that are properly analyzed in this documents, to finally explain the new architecture presented as a solution for distributed environment problems. The new architecture for solving complex solutions in distributed environments presented here is called OBaMADE: Organization Based Multiagent Architecture for Distributed Environments. It is a multiagent architecture based on the organizations of agents paradigm, where the agents in the architecture are structured into organizations to improve their organizational capabilities. The reasoning power of the architecture is based on the Case-Based Reasoning methology, being implemented in a internal organization that uses agents to create services to solve the external request made by the users. The OBaMADE architecture has been successfully applied to two different case studies where its prediction capabilities have been properly checked. Those case studies have showed optimistic results and, being complex systems, have demonstrated the abstraction and generalizations capabilities of the architecture. Nevertheless OBaMADE is intended to be able to solve much other kind of problems in distributed environments scenarios. It should be applied to other varieties of situations and to other knowledge fields to fully develop its potencial.[ES]Los entornos distribuidos representan un campo de conocimiento complejo en el que las soluciones a aplicar deben ser flexibles y deben contar con gran capacidad de adaptación. Este tipo de entornos está normalmente relacionado con problemas donde varios usuarios y dispositivos entran en juego. Para solucionar dichos problemas, pueden utilizarse sistemas locales que, aunque ofrezcan buenos resultados en términos de calidad de los mismos, no son tan efectivos en cuanto a la interacción y posibilidades de uso. Existen múltiples técnicas que pueden ser empleadas para resolver este tipo de problemas, desde CORBA a sistemas multiagente, pasando por servicios web y SOA, entre otros. Todas estas mitologías tienen sus ventajas e inconvenientes, que se analizan en este documento, para explicar, finalmente, la nueva arquitectura presentada como una solución para los problemas generados en entornos distribuidos. La nueva arquitectura aquí se llama OBaMADE, que es el acrónimo del inglés Organization Based Multiagent Architecture for Distributed Environments (Arquitectura Multiagente Basada en Organizaciones para Entornos Distribuidos). Se trata de una arquitectura multiagente basasa en el paradigma de las organizaciones de agente, donde los agentes que forman parte de la arquitectura se estructuran en organizaciones para mejorar sus capacidades organizativas. La capacidad de razonamiento de la arquitectura está basada en la metodología de razonamiento basado en casos, que se ha implementado en una de las organizaciones internas de la arquitectura por medio de agentes que crean servicios que responden a las solicitudes externas de los usuarios. La arquitectura OBaMADE se ha aplicado de forma exitosa a dos casos de estudio diferentes, en los que se han demostrado sus capacidades predictivas. Aplicando OBaMADE a estos casos de estudio se han obtenido resultados esperanzadores y, al ser sistemas complejos, se han demostrado las capacidades tanto de abstracción como de generalización de la arquitectura presentada. Sin embargo, esta arquitectura está diseñada para poder ser aplicada a más tipo de problemas de entornos distribuidos. Debe ser aplicada a más variadas situaciones y a otros campos de conocimiento para desarrollar completamente el potencial de esta arquitectura

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Situated interaction on spatial topics

In this thesis, we present a model and an implementation to handle situational interactions on spatial topics as well as several adaptation strategies to cope with common problems in real-world applications. The model is designed to incorporate situational factors in spatial reasoning processes at the basic level and to facilitate its use in a wide range of applications. The implementation realizing the model corresponds very closely to the structure of the model, and was put to test in a scenario of a mobile tourist guide. The adaptation strategies address the lack of information, resource restrictions as well as the problem of varying availability and quality of positional information.In dieser Arbeit stellen wir ein Modell zur Verarbeitung situierter Interaktionen über raumbezogene Sachverhalte und seine Implementation vor. Außerdem präsentieren wir verschiedene Strategien zum Umgang mit häufigen Problemen, die im Zusammenhang mit dem (mobilen) Einsatz von Systemen im realen Umfeld auftreten. Das zu Grunde liegende Modell bezieht situationsbezogene Faktoren auf unterster Ebene mit ein und erleichtert durch den modularen Aufbau seinen Einsatz im Rahmen verschiedener Anwendungen. Die entsprechende Implementation spiegelt die Struktur des Modells wider und wurde im Rahmen eines mobilen Touristenführers getestet. Die ebenfalls vorgestellten Adaptionsstrategien dienen unter anderem zur Behandlung von Informationsmangel und von Ressourcenbeschränkungen sowie zum Umgang mit dem Problem variierender Verfügbarkeit und Qualität von Positionsinformation

Specialized IoT systems: Models, Structures, Algorithms, Hardware, Software Tools

Монография включает анализ проблем, модели, алгоритмы и программно- аппаратные средства специализированных сетей интернета вещей. Рассмотрены результаты проектирования и моделирования сети интернета вещей, мониторинга качества продукции, анализа звуковой информации окружающей среды, а также технология выявления заболеваний легких на базе нейронных сетей. Монография предназначена для специалистов в области инфокоммуникаций, может быть полезна студентам соответствующих специальностей, слушателям факультетов повышения квалификации, магистрантам и аспирантам

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

Multi-process modelling approach to complex organisation design

Present day markets require manufacturing enterprises (MEs) to be designed and run in a flexibly structured yet optimised way. However, contemporary approaches to ME engineering do not enable this requirement to capture ME attributes such that suitable processes, resource systems and support services can be readily implemented and changed. This study has developed and prototyped a model-driven environment for the design, optimisation and control of MEs with an embedded capability to handle various types of change. This so called Enriched-Process Modelling (E-MPM) Environment can support the engineering of strategic, tactical and operational processes and comprises two parts: (1) an E-MPM Method that informs, structures, and guides modelling activities required at different stages of ME systems design; and (2) an E-MPM Modelling Framework that specifies interconnections between modelling concepts necessary for the design and run time operation of ME systems. [Continues.