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A detailed account of real-time systems, including program structures for real-time, phases development analysis, and formal specification and verification methods of reactive systems. The book brings together the 3 key fields of current and future data-processing: distributed systems and applications, parallel scientific computing, and real-time and manufacturing systems. It covers the basic concepts and theories, methods, techniques and tools currently used in the specification and implementation of applications and contains many examples plus complete case studies.
Fifteen papers were presented at the first workshop on Multi-Agent Systems and Agent-Based Simulation held as part of the Agents World conference in Paris, July 4-- 6, 1998. The workshop was designed to bring together two developing communities: the multi-agent systems researchers who were the core participants at Agents World, and social scientists interested in using MAS as a research tool. Most of the social sciences were represented, with contributions touching on sociology, management science, economics, psychology, environmental science, ecology, and linguistics. The workshop was organised in association with SimSoc, an informal group of social scientists who have arranged an irregular series of influential workshops on using simulation in the social sciences beginning in 1992. While the papers were quite heterogeneous in substantive domain and in their disciplinary origins, there were several themes which recurred during the workshop. One of these was considered in more depth in a round table discussion led by Jim Doran at the end of the workshop on 'Representing cognition for social simulation', which addressed the issue of whether and how cognition should be modelled. Quite divergent views were expressed, with some participants denying that individual cognition needed to be modelled at all, and others arguing that cognition must be at the centre of social simulation.
La conception de systèmes réactifs répond à des impératifs de correction logique (le système fait ce qu'il doit) et de correction temporelle (le système se conforme à un ensemble de contraintes temporelles). Nous proposons dans cet article une approche globale de conception de systèmes réactifs adaptatifs, c'est à dire adaptant dynamiquement leur architecture en fonction du contexte. Pour représenter le comportement des agents composant le système, nous utilisons le formalisme des automates temporisés, ce qui permet d'évaluer à priori les propriétés du système (en termes de correction logique et temporelle), grâce à des techniques de model-checking et de simulation. Des outils de génération automatique de code, que nous avons développés, nous permettent ensuite de produire rapidement, à partir du modèle, un prototype multi-agents opérationnel qui satisfait les mêmes propriétés.
Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW ’99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re?ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi?cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful?lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re?ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci?c application and domain speci?c circumstances to enable knowledge reuse.
This book gathers papers presented at the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD-2018), which was held in Tangiers, Morocco on 12–14 July 2018. In addition to the latest research in the field of energy, it offers new solutions, tools and effective techniques, and provides essential information on smart grids, renewable and economical energy. Further, it addresses modeling, storage management and decision support in the field of energy, offering a valuable guide for researchers, professionals and all those who are interested in the development of advanced intelligent systems in the energy sector.
This book constitutes the refereed proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management, EKAW '99, held at Dagstuhl Castle, Germany in May 1999. The volume presents 16 revised full papers and 15 revised short papers were carefully reviewed and selected form a high number of submissions. Also included are two invited papers. The papers address issues of knowledge acquisition (i.e., the process of extracting, creating, structuring knowledge, etc.), of knowledge-level modeling for knowledge-based systems, and of applying and redefining this work in a knowledge management and knowledge engineering context.