Requirements for Supporting Individual Human Creativity in the Design Domain

International audienceCreativity is an important activity in many professional and leisure domains. This article presents a first step towards a system which will provide a set of tools for enhancing the individual creative abilities of the user in a design task. We have identified aspects which are characterise individual creativity: motivation, domain knowledge, externalization, inspiration and analogies, and requirements handling. Based on these aspects we have defined requirements and suggest associated system functionalities

CLIC: An Agent-Based Interactive and Autonomous Piece of Art

International audienceThis work consists of integrating programming paradigms such as multi-agent systems and rule-based reasoning into a multimedia creation and display platform for interactive artistic creation. It has been developed in order to allow artists to build dynamic and interactive exhibitions based on pictures and sounds and featuring self-evolving and autonomous configurations

Evaluation of Multi-Agent Systems: The case of Interaction

International audienceThis paper deals with the evaluation of Multi-Agent Systems (MAS) at the level of their interaction. Two problems that may be a bias in the evaluation and measurement of interaction are discussed. The first one is the difference between the quantities of information carried by a unit of interaction in two systems having different architectures. The second one concerns the interaction units that are received and cannot be exploited by the agent. In this work, an evaluation based on the weight of the information brought by an interaction is suggested. In order to achieve this, a MAS model, on which the evaluation is based, is defined. Then, the different problems and solutions which will help to evaluate the interaction are studied. Finally, the approach is applied on two different implementations that solve the same problem

Organisation, agrégation et visualisation d'informations médiatiques

International audienceThis article presents some data processing technics for GEOMEDIA, a platform for visualization and analysis of media information. In order to handle the complexity and the large amount of media data, we proceed in three stages. (1) Organization of the information flow in order to extract its global structure: Three dimensions (Agents x Dates x Themes) are settled for data classifying. We use the concept of " agent " , originated from Artificial Intelligence, in order to generalize the concept of " space ". (2) Aggregation of information in order to obtain a macroscopic point of view: Aggregation processes automatically decrease the structural complexity of data. Thus, they generate high-level abstractions. (3) Visualization of aggregated data: spatial projections on geometric, territorial or reticular spaces, temporal projections on timelines, thematic projections on tag clouds, etc.Cet article présente une méthode de traitement de données pour GEOMEDIA, une plateforme de visualisation et d'analyse d'informations médiatiques. Devant la complexité et la quantité des données médiatiques, nous avons trois objectifs. (1) Organisation du déluge d'informations pour en extraire la structure générale : trois dimensions (Agents × Dates × Thèmes) sont retenues pour classer les articles. Nous utilisons la notion d'« agent », issue de l'Intelligence Artificielle, pour généraliser la notion d'« espace ». (2) Agrégation de l'information pour obtenir un point de vue macroscopique sur la structure de données : des procédures automatiques d'agrégation réduisent la complexité structurelle et engendrent ainsi des abstractions de haut-niveaux. (3) Visualisation des données agrégées : projections spatiales sur des cartes géométriques, territoriales ou réticulaires, projections temporelles sur des frises chronologiques, projections thématiques sur des nuages sémantiques, etc

How to Build the Best Macroscopic Description of your Multi-agent System? Application to News Analysis of International Relations

The design and debugging of large-scale MAS require abstraction tools in order to work at a macroscopic level of description. Agent aggregation provides such abstractions by reducing the microscopic description complexity. Since it leads to an information loss, such a key process may be extremely harmful if poorly executed. This research report presents measures inherited from information theory (Kullback-Leibler divergence and Shannon entropy) to evaluate ab- stractions and to provide the experts with feedbacks regarding the generated descriptions. Several evaluation techniques are applied to the spatial aggregation of an agent-based model of international rela- tions. The information from on-line newspapers constitutes a complex microscopic description of agent states. Our approach is able to evalu- ate geographical abstractions used by experts and to deliver them with e cient and meaningful macroscopic descriptions of the world state

A Formal Notion of Objective Expectations in the Context of Multiagent systems Routines

Online edition of New Trends in Artificial Intelligence (ISBN: 978-972-96895-4-3) - Chapter 9: MASTA - Multi-Agent Systems: Theory and ApplicationsInternational audienceThis paper introduces an objective notion of routine expectation, to allow for the external account of expectations in the context of routine procedures, in multiagent systems (MAS). The notion of expectation as usually applied to MAS is briefly reviewed. A formalization of routine procedure is given, so that the formal notion of routine expectation can be defined with respect to actions and facts. A view previously proposed in the literature, to base expectation values on a combination of probability values and utility values, is adopted. However, it is adapted to the context of repetitive, periodic system routines, where utility values can be replaced by the degrees of perfection with which actions and facts are realized

Advances on Practical Applications of Agents and Multiagent Systems

9th International Conference on Practical Applications of Agents and Multiagent Systems, PAAMS 2011, Salamanca,Spain, 6-8 April 2011 (http://www.paams.net/paams2011/) - Proceedings: http://link.springer.com/book/10.1007%2F978-3-642-19875-5International audienceno abstrac

Evaluating Trace Aggregation Through Entropy Measures for Optimal Performance Visualization of Large Distributed Systems

Large-scale distributed high-performance applications are involving an ever-increasing number of threads to explore the extreme concurrency of today's systems. The performance analysis through visualization techniques usually su ers severe semantic limitations due, from one side, to the size of parallel applications, from another side, to the challenges to visualize large-scale traces. Most of performance visualization tools rely therefore on data aggregation in order to be able to scale. Even if this technique is frequently used, to the best of our knowledge, there has not been any real attempt to evaluate the quality of aggregated data for visualization. This paper presents an approach which lls this gap. We propose to build optimized macroscopic visualizations using measures inherited from information theory, and in particular the Kullback-Leibler divergence. These measures are used to estimate the complexity reduced and the information lost during any given data aggregation. We rst illustrate the applicability of our approach by exploiting these two measures in the analysis of work stealing traces using squari ed treemaps. We then report the e ective scalability of our approach by visualizing known anomalies in a synthetic trace le with the behavior of one million processes, with encouraging results

Analyse macroscopique des grands systèmes (émergence épistémique et agrégation spatio-temporelle)

L'analyse des systèmes de grande taille est confrontée à des difficultés d'ordre syntaxique et sémantique : comment observer un million d'entités distribuées et asynchrones ? Comment interpréter le désordre résultant de l'observation microscopique de ces entités ? Comment produire et manipuler des abstractions pertinentes pour l'analyse macroscopique des systèmes ? Face à l'échec de l'approche analytique, le concept d'émergence épistémique - relatif à la nature de la connaissance - nous permet de définir une stratégie d'analyse alternative, motivée par le constat suivant : l'activité scientifique repose sur des processus d'abstraction fournissant des éléments de description macroscopique pour aborder la complexité des systèmes. Cette thèse s'intéresse plus particulièrement à la production d'abstractions spatiales et temporelles par agrégation de données. Afin d'engendrer des représentations exploitables lors du passage à l'échelle, il apparaît nécessaire de contrôler deux aspects essentiels du processus d'abstraction. Premièrement, la complexité et le contenu informationnel des représentations macroscopiques doivent être conjointement optimisés afin de préserver les détails pertinents pour l'observateur, tout en minimisant le coût de l'analyse. Nous proposons des mesures de qualité (critères internes) permettant d'évaluer, de comparer et de sélectionner les représentations en fonction du contexte et des objectifs de l'analyse. Deuxièmement, afin de conserver leur pouvoir explicatif, les abstractions engendrées doivent être cohérentes avec les connaissances mobilisées par l'observateur lors de l'analyse. Nous proposons d'utiliser les propriétés organisationnelles, structurelles et topologiques du système (critères externes) pour contraindre le processus d'agrégation et pour engendrer des représentations viables sur les plans syntaxique et sémantique. Par conséquent, l'automatisation du processus d'agrégation nécessite de résoudre un problème d'optimisation sous contraintes. Nous proposons dans cette thèse un algorithme de résolution générique, s'adaptant aux critères formulés par l'observateur. De plus, nous montrons que la complexité de ce problème d'optimisation dépend directement de ces critères. L'approche macroscopique défendue dans cette thèse est évaluée sur deux classes de systèmes. Premièrement, le processus d'agrégation est appliqué à la visualisation d'applications parallèles de grande taille pour l'analyse de performance. Il permet de détecter les anomalies présentes à plusieurs niveaux de granularité dans les traces d'exécution et d'expliquer ces anomalies à partir des propriétés syntaxiques du système. Deuxièmement, le processus est appliqué à l'agrégation de données médiatiques pour l'analyse des relations internationales. L'agrégation géographique et temporelle de l'attention médiatique permet de définir des évènements macroscopiques pertinents sur le plan sémantique pour l'analyse du système international. Pour autant, nous pensons que l'approche et les outils présentés dans cette thèse peuvent être généralisés à de nombreux autres domaines d'application.The analysis of large-scale systems faces syntactic and semantic difficulties: How to observe millions of distributed and asynchronous entities? How to interpret the disorder that results from the microscopic observation of such entities? How to produce and handle relevant abstractions for the systems' macroscopic analysis? Faced with the failure of the analytic approach, the concept of epistemic emergence - related to the nature of knowledge - allows us to define an alternative strategy. This strategy is motivated by the observation that scientific activity relies on abstraction processes that provide macroscopic descriptions to broach the systems' complexity. This thesis is more specifically interested in the production of spatial and temporal abstractions through data aggregation. In order to generate scalable representations, the control of two essential aspects of the aggregation process is necessary. Firstly, the complexity and the information content of macroscopic representations should be jointly optimized in order to preserve the relevant details for the observer, while minimizing the cost of the analysis. We propose several measures of quality (internal criteria) to evaluate, compare and select the representations depending on the context and the objectives of the analysis. Secondly, in order to preserve their explanatory power, the generated abstractions should be consistent with the background knowledge exploited by the observer for the analysis. We propose to exploit the systems' organisational, structural and topological properties (external criteria) to constrain the aggregation process and to generate syntactically and semantically consistent representations. Consequently, the automation of the aggregation process requires solving a constrained optimization problem. We propose a generic algorithm that adapts to the criteria expressed by the observer. Furthermore, we show that the complexity of this optimization problem directly depend on these criteria. The macroscopic approach supported by this thesis is evaluated on two classes of systems. Firstly, the aggregation process is applied to the visualisation of large-scale distributed applications for performance analysis. It allows the detection of anomalies at several scales in the execution traces and the explanation of these anomalies according to the system syntactic properties. Secondly, the process is applied to the aggregation of news for the analysis of international relations. The geographical and temporal aggregation of media attention allows the definition of semantically consistent macroscopic events for the analysis of the international system. Furthermore, we believe that the approach and the tools presented in this thesis can be extended to a wider class of application domains.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF