Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Monitoring morphisms to support sustainable interoperability of enterprise systems

Dissertation to obtain the Master degree in Electrical Engineering and Computer Science

Desenvolvimento de uma framework de argumentação Para apoio à tomada de decisão ubíqua

Os Sistemas de Apoio à Tomada de Decisão em Grupo (SADG) surgiram com o objetivo de apoiar um conjunto de decisores no processo de tomada de decisão. Uma das abordagens mais comuns na literatura para a implementação dos SADG é a utilização de Sistemas Multi-Agente (SMA). Os SMA permitem refletir com maior transparência o contexto real, tanto na representação que cada agente faz do decisor que representa como no formato de comunicação utilizado. Com o crescimento das organizações, atualmente vive-se uma viragem no conceito de tomada de decisão. Cada vez mais, devido a questões como: o estilo de vida, os mercados globais e o tipo de tecnologias disponíveis, faz sentido falar de decisão ubíqua. Isto significa que o decisor deverá poder utilizar o sistema a partir de qualquer local, a qualquer altura e através dos mais variados tipos de dispositivos eletrónicos tais como tablets, smartphones, etc. Neste trabalho é proposto um novo modelo de argumentação, adaptado ao contexto da tomada de decisão ubíqua para ser utilizado por um SMA na resolução de problemas multi-critério. É assumido que cada agente poderá utilizar um estilo de comportamento que afeta o modo como esse agente interage com outros agentes em situações de conflito. Sendo assim, pretende-se estudar o impacto da utilização de estilos de comportamento ao longo do processo da tomada de decisão e perceber se os agentes modelados com estilos de comportamento conseguem atingir o consenso mais facilmente quando comparados com agentes que não apresentam nenhum estilo de comportamento. Pretende-se ainda estudar se o número de argumentos trocados entre os agentes é proporcional ao nível de consenso final após o processo de tomada de decisão. De forma a poder estudar as hipóteses de investigação desenvolveu-se um protótipo de um SADG, utilizando um SMA. Desenvolveu-se ainda uma framework de argumentação que foi adaptada ao protótipo desenvolvido. Os resultados obtidos permitiram validar as hipóteses definidas neste trabalho tendo-se concluído que os agentes modelados com estilos de comportamento conseguem na maioria das vezes atingir um consenso mais facilmente comparado com agentes que não apresentam nenhum estilo de comportamento e que o número de argumentos trocados entre os agentes durante o processo de tomada de decisão não é proporcional ao nível de consenso final.

An agent based architecture for material handling systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Negotiation environment to support enterprise interoperability sustainability

Dissertation to obtain the Master degree in Electrical Engineering and Computer Science

Lightweight robust behavior industrial agent methodology

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Transactions in dynamic reactive environments

Most of today’s systems, especially when related to the Web or to multi-agent systems, are not standalone or independent, but are part of a greater ecosystem, where they need to interact with other entities, react to complex changes in the environment, and act both over its own knowledge base and on the external environment itself. Moreover, these systems are clearly not static, but are constantly evolving due to the execution of self updates or external actions. Whenever actions and updates are possible, the need to ensure properties regarding the outcome of performing such actions emerges. Originally purposed in the context of databases, transactions solve this problem by guaranteeing atomicity, consistency, isolation and durability of a special set of actions. However, current transaction solutions fail to guarantee such properties in dynamic environments, since they cannot combine transaction execution with reactive features, or with the execution of actions over domains that the system does not completely control (thus making rolling back a non-viable proposition). In this thesis, we investigate what and how transaction properties can be ensured over these dynamic environments. To achieve this goal, we provide logic-based solutions, based on Transaction Logic, to precisely model and execute transactions in such environments, and where knowledge bases can be defined by arbitrary logic theories.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Modelado multi-dominio de máquinas eléctricas. Multi-domain modeling of electric machines

El objetivo general de este proyecto es desarrollar nuevos modelos multi-dominio de máquinas eléctricas para aplicaciones al control y al diagnóstico de fallas. Se propone comenzar con el modelo electromagnético del motor de inducción en base a circuitos magnéticos equivalentes (MEC) validándolo por medio de simulación y de resultados experimentales. Como segundo paso se pretende desarrollas modelos térmicos y mecánicos con el objetivo que puedan ser acoplados al modelo electromagnético y de esta estudiar la interacción de los dominios y se validará mediante resultados de simulación y experimentales el modelo completo. Finalmente se pretende utilizar el modelo multi-dominio como una herramienta para la prueba de nuevas estrategias de control y diagnóstico de fallas. The main objective of this project is the development of new multi-domain models of electric machines for control and fault diagnosis applications. The electromagnetic modeling of the induction motor (IM) will be done using the magnetic equivalent circuits approach. This model will be validated by simulation and by experimental results. As a second step of this project, new mechanical and thermal models for the IM will be developed, with the objective of coupling these models with the electromagnetic one. With this multi-domain model it will be possible to study the interaction between each others. After that, the complete model will be validated by simulation and experimental results. Finally, the model will be used as a tool for testing new control and fault diagnosis strategies.

Adaptive intelligent agent approach to guide the web navigation on the PLAN-G distance learning platform

Hypermedia systems based on the Web for open distance education are becoming increasinglypopular as tools for user-driven access learning information. Adaptive hypermedia is a new direction in research within the area of user-adaptive systems, to increase its functionality by making it personalized [Eklu 961. This paper sketches a general agents architecture to include navigationaladaptability and user-friendly processes which would guide and accompany the student during hislher learning on the PLAN-G hypermedia system (New Generation Telematics Platform to Support Open and Distance Learning), with the aid of computer networks and specifically WWW technology [Marz 98-1] [Marz 98-2]. The PLAN-G actual prototype is successfully used with some informatics courses (the current version has no agents yet). The propased multi-agent system, contains two different types of adaptive autonomous software agents: Personal Digital Agents {Interface), to interacl directly with the student when necessary; and Information Agents (Intermediaries), to filtrate and discover information to learn and to adapt navigation space to a specific student

Steady-state brain glucose transport kinetics re-evaluated with a four-state conformational model.

Glucose supply from blood to brain occurs through facilitative transporter proteins. A near linear relation between brain and plasma glucose has been experimentally determined and described by a reversible model of enzyme kinetics. A conformational four-state exchange model accounting for trans-acceleration and asymmetry of the carrier was included in a recently developed multi-compartmental model of glucose transport. Based on this model, we demonstrate that brain glucose (G(brain)) as function of plasma glucose (G(plasma)) can be described by a single analytical equation namely comprising three kinetic compartments: blood, endothelial cells and brain. Transport was described by four parameters: apparent half saturation constant K(t), apparent maximum rate constant T(max), glucose consumption rate CMR(glc), and the iso-inhibition constant K(ii) that suggests G(brain) as inhibitor of the isomerisation of the unloaded carrier. Previous published data, where G(brain) was quantified as a function of plasma glucose by either biochemical methods or NMR spectroscopy, were used to determine the aforementioned kinetic parameters. Glucose transport was characterized by K(t) ranging from 1.5 to 3.5 mM, T(max)/CMR(glc) from 4.6 to 5.6, and K(ii) from 51 to 149 mM. It was noteworthy that K(t) was on the order of a few mM, as previously determined from the reversible model. The conformational four-state exchange model of glucose transport into the brain includes both efflux and transport inhibition by G(brain), predicting that G(brain) eventually approaches a maximum concentration. However, since K(ii) largely exceeds G(plasma), iso-inhibition is unlikely to be of substantial importance for plasma glucose below 25 mM. As a consequence, the reversible model can account for most experimental observations under euglycaemia and moderate cases of hypo- and hyperglycaemia.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Automated monitoring of medical protocols: a secure and distributed architecture

The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

Social control of public expenditures in a multilevel principal-agent approach

ABSTRACTThis study enhances the principal-agent model by incorporating a multilevel perspective and differences among agency situations. A theoretical discussion is developed using a proposed intersection of methodological focuses and a descriptive-exemplificative hypothetical analysis. The analysis is applied to public expenditure social control in representative democracies, and as a result, a principal-agent model unfolds that incorporates a decision-making perspective and focuses on formulation, negotiation, articulation, and implementation competencies. Thus, it is possible to incorporate elements into the principal-agent model to make it more permeable to individual, group, and societal idiosyncrasies with respect to public expenditure social control.

The Conceptualization and Exploration of Place Allegiance: Towards a Unified Model of Person-Place Relationships within Outdoor Recreation

The academic study of place has been generally defined by two distinct and highly refined discourses within outdoor recreation research: place attachment and sense of place. Place attachment generally describes the intensity of the place relationship, whereas sense of place approaches place from a more holistic and intimate orientation. This study bridges these two methodological and theoretical separate areas of place research together by re-conceptualizing the way in which place relationships are viewed within outdoor recreation research. The Psychological Continuum Model is used to extend the language of place attachment to incorporate more of the philosophy of sense of place while attending to the empirical strength and utility of place attachment. This extension results in the term place allegiance being coined to depict the strong and profound relationships outdoor recreationists build with their places of outdoor recreation. Using a concurrent mixed methods research design, this study explored place allegiance via an online survey (n = 437) and thirteen in-depth qualitative interviews with outdoor recreationists. Results indicate that place allegiance can be measured through a multi-dimensional model of place allegiance that incorporates behaviours, importance, resistance, knowledge and symbolic value. In addition, place allegiance was found to be related to an individual's influence on life course and his/her willingness to exhibit preservation and protection tendencies. Place allegiance plays an important role in acknowledging the importance of authentic place relationships in an effort to confront placelessness. Wilderness recreation is an important avenue for outdoor recreationists to build strong place relationships.