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Start Over Topic 0202 electrical engineering, electronic engineering, information engineering Topic business Language undetermined Publisher hal ccsd
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1. Domain-Specific Modeling for a Crop Model Factory

Author

François Pinet, David R.C. Hill, Véronique Cucchi, Guillaume Barbier, ITK [Clapiers], Technologies et systèmes d'information pour les agrosystèmes (UR TSCF), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Ecole Nationale Supérieure des Mines de St Etienne-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), and Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])

Subjects
Engineering, business.industry, Interface (Java), Process (engineering), Design pattern, [SDV]Life Sciences [q-bio], Domain-specific modeling, 020207 software engineering, Context (language use), 04 agricultural and veterinary sciences, 02 engineering and technology, Data structure, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Metamodeling, 040103 agronomy & agriculture, 0202 electrical engineering, electronic engineering, information engineering, 0401 agriculture, forestry, and fisheries, Factory (object-oriented programming), [INFO]Computer Science [cs], business, Software engineering, Simulation, Information Systems
Abstract

[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]MOTIVE; In the context of crop model design for industrial purposes, this paper proposes a domain-specific modeling approach to provide a crop model factory for the modelers in agronomy. The authors’ approach proposes to separate the concerns of representing the simulation process (process-based dynamics) and the plant data structure. They propose a refined and stabilized metamodel for the dynamics based on past preliminary work. This paper also explains how the Model-View-Controller design pattern can be applied to DSML environments to produce a more specialist-friendly interface. In addition, the authors propose a metamodeling usage of the Model-View-Controller offering the potential to develop a DSML for DSMLs design.

Published
2013

2. Towards a dialectical approach for conversational agents in selling situations

Author

Sameh Abdel-Naby, Bruno Beaufils, Maxime Morge, Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Systèmes Multi-Agents et Comportements (SMAC), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Dipartimento di Informatica [Pisa], University of Pisa - Università di Pisa, Dipartimento di Informatica [Pisa] (DI), Department of Information Engineering and Computer Science (DISI), University of Trento [Trento], Dipartimento di Ingegneria e Scienza dell'Informazione (DISI), Università degli Studi di Trento (UNITN), McBurney, Peter and Rahwan, Iyad and Parsons, Simon, Lifl, Hal, and McBurney, Peter and Rahwan, Iyad and Parsons, Simon

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [QFIN.GN] Quantitative Finance [q-fin]/General Finance [q-fin.GN], [INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO], Knowledge management, Computer science, Interface (Java), 0102 computer and information sciences, 02 engineering and technology, E-commerce, computer.software_genre, 01 natural sciences, Argumentation theory, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Intelligent agent, 0202 electrical engineering, electronic engineering, information engineering, Product (category theory), Dialectic, Service (business), [QFIN.GN]Quantitative Finance [q-fin]/General Finance [q-fin.GN], [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], business.industry, [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], [INFO.INFO-CE] Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], 010201 computation theory & mathematics, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], [INFO.INFO-GT] Computer Science [cs]/Computer Science and Game Theory [cs.GT], 020201 artificial intelligence & image processing, [INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA], business, computer
Abstract

The use of virtual agents to intelligently interface with online customers of e-commerce businesses is remarkably increasing. Most of these virtual agents are designed to assist online customers while searching for information related to a specific product or service, while few agents are intended for promoting and selling a product or a service. Within the later type, our aim is to provide proactive agents that recommend a specific item and justify this recommendation to a customer based on his purchases history and his needs. In this paper, we propose a dialectical argumentation approach that would allow virtual agents that have sales goals to trigger persuasions with e-commerce's customers. Then, we illustrate the proposed idea through its integration with an example from real-life. Categories and Subject Descriptors I.2.11 [Artificial Intelligence:] Intelligent Agents. General Terms: Algorithms.

Published
2010

3. Generating Various And Consistent Behaviors In Simulations

Author

Philippe Mathieu, Andras Kemeny, Benoît Lacroix, Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Systèmes Multi-Agents et Comportements (SMAC), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Technocentre Renault [Guyancourt], RENAULT, Demazeau, Yves and Pavòn, Juan and Corchado, Juan and Bajo, and Javier

Subjects
[QFIN.GN]Quantitative Finance [q-fin]/General Finance [q-fin.GN], [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], Computer science, business.industry, Process (engineering), [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], Mechanism based, Traffic simulation, [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], 020207 software engineering, 02 engineering and technology, Machine learning, computer.software_genre, Determinism, Variety (cybernetics), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Consistency (database systems), Software, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], 0202 electrical engineering, electronic engineering, information engineering, Unsupervised learning, 020201 artificial intelligence & image processing, Artificial intelligence, business, computer
Abstract

In multi-agent based simulations, providing various and consistent behaviors for the agents is an important issue to produce realistic and valid results. However, it is difficult for the simulations users to manage simultaneously these two elements, especially when the exact influence of each behaviorial parameter remains unknown. We propose in this paper a generic model designed to deal with this issue: easily generate various and consistent behaviors for the agents. The behaviors are described using a normative approach, which allows increasing the variety by introducing violations. The generation engine controls the determinism of the creation process, and a mechanism based on unsupervised learning allows managing the behaviors consistency. The model has been applied to traffic simulation with the driving simulation software used at Renault, scaner© ii, and experimental results are presented to demonstrate its validity.

Published
2009

4. Towards a Pragmatic Methodology for Open Multi-agent Systems

Author

Yann Secq, Philippe Mathieu, Jean-Christophe Routier, Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Systèmes Multi-Agents et Comportements (SMAC), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Zhong, Ning and Ra\'s, Zbigniew W. and Tsumoto, Shusaku and Suzuki, and Einoshin

Subjects
[QFIN.GN]Quantitative Finance [q-fin]/General Finance [q-fin.GN], Thesaurus (information retrieval), [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], business.industry, Computer science, Multi-agent system, Interoperability, [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], Interaction protocol, 02 engineering and technology, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, Software engineering, business
Abstract

This paper introduces the Rio methodology, which relies on the notions of Role, Interaction and Organization. We define a model of runnable specification of interaction protocols that represents interactions between agents globally, and that can be processed in orsder to generate Colored Petri Nets that handle agent conversations. Moreover, these specifications are not tied to a particular agent model and could therefore be used to enable multi-agent systems interoperability.

Published
2003

5. A Multi-Agent Approach to Co-operative Work

Author

Jean-Christophe Routier, Philippe Mathieu, Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Systèmes Multi-Agents et Comportements (SMAC), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Kolski, Christophe and Vanderdonckt, and Jean

Subjects
[QFIN.GN]Quantitative Finance [q-fin]/General Finance [q-fin.GN], Collaborative software, [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], business.industry, Interface (Java), Computer science, [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], 02 engineering and technology, Multi agent approach, Task (project management), User interface design, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Work (electrical), Human–computer interaction, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, User interface, business, Programmer
Abstract

This paper presents a multi-agent approach for user interface design of co-operative applications. We show here that this approach provides advantages from multi-agent researches about intelligence and modeling. It allows the designer to develop more easily the user interface of his application. Two different aspects are improved: first, the management of the interactions between components of the interface and second, the interactions between the user and the application, in particular thanks to intelligent assistants. Moreover, an agent oriented analysis of the problem highlights the different role and skills and thus eases the programmer task and the evolution capacity of the application. To illustrate our purpose, we present a co-operative work application built with our multi-agent development framework, called Magique. The main goal of this article is not really to present a groupware application but rather to show how it can be easily developed, maintained and extended thanks to Magique and its multi-agent approach

Published
2002

6. Exact Knowledge Compilation in Predicate Calculus: the Partial Achievement Case

Author

Olivier Roussel, Philippe Mathieu, Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Systèmes Multi-Agents et Comportements (SMAC), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Informatique de Lens (CRIL), Centre National de la Recherche Scientifique (CNRS)-Université d'Artois (UA), and Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Zeroth-order logic, Inference, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Forward chaining, 0202 electrical engineering, electronic engineering, information engineering, Calculus, Knowledge compilation, Modus ponens, Mathematics, [QFIN.GN]Quantitative Finance [q-fin]/General Finance [q-fin.GN], [INFO.INFO-GT]Computer Science [cs]/Computer Science and Game Theory [cs.GT], business.industry, [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], Propositional calculus, First-order logic, TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES, Knowledge base, 010201 computation theory & mathematics, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], 020201 artificial intelligence & image processing, business, Algorithm
Abstract

Forward chaining is an inference algorithm based on modus ponens which is widely used but unfortunately incomplete with respect to the usual boolean logic. A solution to this incompleteness is to compile the knowledge base so that forward chaining becomes complete for any base of facts. This compilation is called achievement and was so far restricted to propositional calculus. In this paper, we extend this compilation method to the predicate calculus. To our knowledge, this is the first exact knowledge compilation for first order logic.

Published
1997