Software Components for Signal Fishing based on GA Element Position Optimizer

Long-term adaptation solutions do not receive much attention in the design phase of a wireless system. A new approach is proposed, where the antenna takes an active role in characterising and learning the operation environment. The proposed solution is based on a signal fishing mechanism. Several software components, among which a genetic optimizer, implement the processing stages of autonomous design of the antenna array during operation

Training the Behaviour Preferences on Context Changes

Personalized ambient intelligent systems should meet changes in user’s needs, which evolve over time. Our objective is to create an adaptive system that learns the user behaviour preferences. We propose *BAM – * Behaviour Adaptation Mechanism, a neural-network based control system that is trained, supervised by user’s (affective) feedback in real-time. The system deduces the preferred behaviour, based on the detection of affective state’s valence (negative, neutral and positive) from facial features analysis. The neural network is retrained periodically with the updated training set, obtained from the interpretation of the user’s reaction to the system’s decisions. We investigated how many training examples, rendered from user’s behaviour, are required in order to train the neural network so that it reaches an accuracy of at least 75%. We present the evolution of behaviour preference learning parameters when the number of context elements increases

Adaptation dynamique de services

This paper proposes a software architecture for dynamical service adaptation. The services are constituted by reusable software components. The adaptation's goal is to optimize the service function of their execution context. For a first step, the context will take into account just the user needs but other elements will be added. A particular feature in our proposition is the profiles that are used not only to describe the context's elements but also the components itself. An Adapter analyzes the compatibility between all these profiles and detects the points where the profiles are not compatibles. The same Adapter search and apply the possible adaptation solutions: component customization, insertion, extraction or replacement

Natural Language based On-demand Service Composition

The widespread of Web services in the ubiquitous computing era and the impossibility to predict a priori all possible user needs generates the necessity for on-demand service composition. Natural language is one of the the easiest ways for a user to express what he expects regarding a service. Two main problems need to be solved in order to create a composite service to satisfy the user: a)retrieval of relevant services and b) orchestration/composition of the selected services in order to fulfill the user request. We solve the first problem by using semantic concepts associated with the services and we define a conceptual distance to measure the similarity between the user request and a service configuration. Retrieved services are composed, based on aspect oriented templates called Aspects of Assembly. We have tested our application in an environment for pervasive computing called Ubiquarium, where our system composes a service according to the user request described by a sentence. The implementation is based on the WComp middleware that enables us to use regular Web services but also Web services for devices

A strategic interaction model of punishment favoring contagion of honest behavior.

The punishment effect on social behavior is analyzed within the strategic interaction framework of Cellular Automata and computational Evolutionary Game Theory. A new game, called Social Honesty (SH), is proposed. The SH game is analyzed in spatial configurations. Probabilistic punishment is used as a dishonesty deterrence mechanism. In order to capture the intrinsic uncertainty of social environments, payoffs are described as random variables. New dynamics, with a new relation between punishment probability and punishment severity, are revealed. Punishment probability proves to be more important than punishment severity in guiding convergence towards honesty as predominant behavior. This result is confirmed by empirical evidence and reported experiments. Critical values and transition intervals for punishment probability and severity are identified and analyzed. Clusters of honest or dishonest players emerge spontaneously from the very first rounds of interaction and are determinant for the future dynamics and outcomes

-transition intervals for different types of neighborhoods.

<p>von Neumann (r = 1,2), Moore (r = 1,2,3) well-mixed (everybody is neighbor with everybody) and scale-free (power law connections mapped on the lattice). Averaged values for 100 runs are observed after 500 game rounds.</p

Variation of -player rate with the punishment severity .

<p>Averaged values for 100 runs are observed after 500 game rounds. Punishment probability is: , and . The game starts with 50%, randomly distributed, -players.</p

Adaptation dynamique de services (Complément de titre)

Nous avons choisi de traiter dans cette thèse les problèmes liés à l'adaptation dynamique de services assemblés par des composants réutilisables. L'adaptation de services est nécessaire parce que le fonctionnement des services dépend de leur contexte d'utilisation (profils utilisateurs, ressources disponibles, etc.). Le contexte évolue dans le temps alors que le service est en cours d'exécution, l'adaptation doit par conséquent être réalisée dynamiquement. L'analyse de solutions existantes nous a conduits à plusieurs conclusions. La plus importante est que la partie de contrôle de l'adaptation ne peut être construit a priori. L'objectif de la thèse est de proposer une autre solution qui permet à un service de pouvoir être adapté à un contexte qui n'a pas été pris en compte initialement. Pour tester notre proposition nous avons construit un prototype basé sur l'étude de plusieurs scénariosThis thesis approaches dynamic adaptation issues of services assembled of reusable software components. Service adaptation is necessary because their functioning depends on the context in which they are used. The context is made up of external components that can influence the service, such as : the user, the device, the geographical environment and others. The context evolves during service execution and that is why the service has to adapt dynamically to the context evolution. The analysis of existing solutions has lead to several conclusions among which the most important is that the control part of service adaptation platforms follows an approach that we call "planned approach". In the case of a planned adaptation approach the context has to be known apriori and the way the service reacts to possible contexts is planned by the service builder and specified in the form of roles and strategies which are specific to each service. The aim of this thesis is to propose a solution for unplanned service adaptation, meaning the possibility of adaptation to a context that is not entirely anticipated at the moment of service building. Unlike the planned approach, where the adaptation roles and strategies have to be established for each service separately, we want these roles and strategies to be general and service independent. In order to test our proposaI we have built a prototype based on the implementation of several adaptation scenariosCHAMBERY -BU Bourget (730512101) / SudocSudocFranceF

Experimental -transition intervals.

<p>Experimental -transition intervals for , and . The game starts with 50% -players randomly distributed. Average -player rate values for 100 runs are observed after 500 game rounds.</p