Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

A mobile robot platform for open learning based on serious games and remote laboratories

Within the pedagogical community, Serious Games have arisen as a viable alternative to traditional course-based learning materials. Until now, they have been based strictly on software solutions. Meanwhile, research into Remote Laboratories has shown that they are a viable, low-cost solution for experimentation in an engineering context, providing uninterrupted access, low-maintenance requirements, and a heightened sense of reality when compared to simulations. This paper will propose a solution where both approaches are combined to deliver a Remote Laboratory-based Serious Game for use in engineering and school education. The platform for this system is the WebLab-Deusto Framework, already well-tested within the remote laboratory context, and based on open standards. The laboratory allows users to control a mobile robot in a labyrinth environment and take part in an interactive game where they must locate and correctly answer several questions, the subject of which can be adapted to educators' needs. It also integrates the Google Blockly graphical programming language, allowing students to learn basic programming and logic principles without needing to understand complex syntax.

Multi-agent system for personalization of location-based services

The current ubiquitous network access and increase in network bandwidth are driving the sales of mobile location-aware user devices and, consequently, the development of context-aware applications, namely location-based services. The goal of this project is to provide consumers of location-based services with a richer end-user experience by means of service composition, personalization, device adaptation and continuity of service. Our approach relies on a multi-agent system composed of proxy agents that act as mediators and providers of personalization meta-services, device adaptation and continuity of service for consumers of pre-existing location-based services. These proxy agents, which have Web services interfaces to ensure a high level of interoperability, perform service composition and take in consideration the preferences of the users, the limitations of the user devices, making the usage of different types of devices seamless for the end-user. To validate and evaluate the performance of this approach, use cases were defined, tests were conducted and results gathered which demonstrated that the initial goals were successfully fulfilled.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Realistic Multi-Agent Simulation of Competitive Electricity Markets

The dynamism and ongoing changes that the electricity markets sector is constantly suffering, enhanced by the huge increase in competitiveness, create the need of using simulation platforms to support operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents an enhanced electricity market simulator, based on multi-agent technology, which provides an advanced simulation framework for the study of real electricity markets operation, and the interactions between the involved players. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) uses real data for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations bring to different countries. Also, the development of an upper-ontology to support the communication between participating agents, provides the means for the integration of this simulator with other frameworks, such as MAN-REM (Multi-Agent Negotiation and Risk Management in Electricity Markets). A case study using the enhanced simulation platform that results from the integration of several systems and different tools is presented, with a scenario based on real data, simulating the MIBEL electricity market environment, and comparing the simulation performance with the real electricity market results.

Development of an enzyme immobilization platform based on microencapsulation for paper-based biosensors

Un papier bioactif est obtenu par la modification d’un papier en y immobilisant une ou plusieurs biomolécules. La recherche et le développement de papiers bioactifs est en plein essor car le papier est un substrat peu dispendieux qui est déjà d’usage très répandu à travers le monde. Bien que les papiers bioactifs n’aient pas connus de succès commercial depuis la mise en marche de bandelettes mesurant le taux de glucose dans les années cinquante, de nombreux groupes de recherche travaillent à immobiliser des biomolécules sur le papier pour obtenir un papier bioactif qui est abordable et possède une bonne durée de vie. Contrairement à la glucose oxidase, l’enzyme utilisée sur ces bandelettes, la majorité des biomolécules sont très fragiles et perdent leur activité très rapidement lorsqu’immobilisées sur des papiers. Le développement de nouveaux papiers bioactifs pouvant détecter des substances d’intérêt ou même désactiver des pathogènes dépend donc de découverte de nouvelles techniques d’immobilisation des biomolécules permettant de maintenir leur activité tout en étant applicable dans la chaîne de production actuelle des papiers fins. Le but de cette thèse est de développer une technique d’immobilisation efficace et versatile, permettant de protéger l’activité de biomolécules incorporées sur des papiers. La microencapsulation a été choisie comme technique d’immobilisation car elle permet d’enfermer de grandes quantités de biomolécules à l’intérieur d’une sphère poreuse permettant leur protection. Pour cette étude, le polymère poly(éthylènediimine) a été choisi afin de générer la paroi des microcapsules. Les enzymes laccase et glucose oxidase, dont les propriétés sont bien établies, seront utilisées comme biomolécules test. Dans un premier temps, deux procédures d’encapsulation ont été développées puis étudiées. La méthode par émulsion produit des microcapsules de plus petits diamètres que la méthode par encapsulation utilisant un encapsulateur, bien que cette dernière offre une meilleure efficacité d’encapsulation. Par la suite, l’effet de la procédure d’encapsulation sur l’activité enzymatique et la stabilité thermique des enzymes a été étudié à cause de l’importance du maintien de l’activité sur le développement d’une plateforme d’immobilisation. L’effet de la nature du polymère utilisé pour la fabrication des capsules sur la conformation de l’enzyme a été étudié pour la première fois. Finalement, l’applicabilité des microcapsules de poly(éthylèneimine) dans la confection de papiers bioactifs a été démontré par le biais de trois prototypes. Un papier réagissant au glucose a été obtenu en immobilisant des microcapsules contenant l’enzyme glucose oxidase. Un papier sensible à l’enzyme neuraminidase pour la détection de la vaginose bactérienne avec une plus grande stabilité durant l’entreposage a été fait en encapsulant les réactifs colorimétriques dans des capsules de poly(éthylèneimine). L’utilisation de microcapsules pour l’immobilisation d’anticorps a également été étudiée. Les avancées au niveau de la plateforme d’immobilisation de biomolécules par microencapsulation qui ont été réalisées lors de cette thèse permettront de mieux comprendre l’effet des réactifs impliqués dans la procédure de microencapsulation sur la stabilité, l’activité et la conformation des biomolécules. Les résultats obtenus démontrent que la plateforme d’immobilisation développée peut être appliquée pour la confection de nouveaux papiers bioactifs.

A Negotiation Style Recommender Based on Computational Ecology in Open Negotiation Environments

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies

Decoration of au and ag nanoparticles on self-assembling pseudopeptide-based nanofiber by using a short peptide as capping agent for metal nanoparticles

The surface of a nanofiber that is formed from a self-assembling pseudopeptide has been decorated by gold and silver nanoparticles that are stabilized by a dipeptide. Transmission electron microscopic images make the decoration visible. In this paper, a new strategy of mineralizing a pseudopeptide based nanofiber by gold and silver nanoparticles with use of a two-component nanografting method is described.

Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Queue-based agent architecture for multimodal interfaces

This paper presents a queue-based agent architecture for multimodal interfaces. Using a novel approach to intelligently organise both agents and input data, this system has the potential to outperform current state-of-the-art multimodal systems, while at the same time allowing greater levels of interaction and flexibility. This assertion is supported by simulation test results showing that significant improvements can be obtained over normal sequential agent scheduling architectures. For real usage, this translates into faster, more comprehensive systems, without the limited application domain that restricts current implementations.

Queue-based agent communication architecture for intelligent human-like computer interfaces

Human-like computer interaction systems requires far more than just simple speech input/output. Such a system should communicate with the user verbally, using a conversational style language. It should be aware of its surroundings and use this context for any decisions it makes. As a synthetic character, it should have a computer generated human-like appearance. This, in turn, should be used to convey emotions, expressions and gestures. Finally, and perhaps most important of all, the system should interact with the user in real time, in a fluent and believable manner.