425 research outputs found
Knowledge revision in systems based on an informed tree search strategy : application to cartographic generalisation
Many real world problems can be expressed as optimisation problems. Solving
this kind of problems means to find, among all possible solutions, the one that
maximises an evaluation function. One approach to solve this kind of problem is
to use an informed search strategy. The principle of this kind of strategy is
to use problem-specific knowledge beyond the definition of the problem itself
to find solutions more efficiently than with an uninformed strategy. This kind
of strategy demands to define problem-specific knowledge (heuristics). The
efficiency and the effectiveness of systems based on it directly depend on the
used knowledge quality. Unfortunately, acquiring and maintaining such knowledge
can be fastidious. The objective of the work presented in this paper is to
propose an automatic knowledge revision approach for systems based on an
informed tree search strategy. Our approach consists in analysing the system
execution logs and revising knowledge based on these logs by modelling the
revision problem as a knowledge space exploration problem. We present an
experiment we carried out in an application domain where informed search
strategies are often used: cartographic generalisation.Comment: Knowledge Revision; Problem Solving; Informed Tree Search Strategy;
Cartographic Generalisation., Paris : France (2008
Using Computational Agents to Design Participatory Social Simulations
In social science, the role of stakeholders is increasing in the development and use of simulation models. Their participation in the design of agent-based models (ABMs) has widely been considered as an efficient solution to the validation of this particular type of model. Traditionally, "agents" (as basic model elements) have not been concerned with stakeholders directly but via designers or role-playing games (RPGs). In this paper, we intend to bridge this gap by introducing computational or software agents, implemented from an initial ABM, into a new kind of RPG, mediated by computers, so that these agents can interact with stakeholders. This interaction can help not only to elicit stakeholders' informal knowledge or unpredicted behaviours, but also to control stakeholders' focus during the games. We therefore formalize a general participatory design method using software agents, and illustrate it by describing our experience in a project aimed at developing agent-based social simulations in the field of air traffic management.Participatory Social Simulations, Agent-Based Social Simulations, Computational Agents, Role-Playing Games, Artificial Maieutics, User-Centered Design
Methods for Agent-Based Computer Modelling
International audiencePlenary Session of the Tam Dao University
The MICRoBES Project, an Experimental Approach towards 'Open Collective Robotics'
International audienceWe focus here on "Open Collective Robotics", a research domain interested in studying concepts and techniques which could lead to true collectivities between humans and robots. We also present the MICRobES project, a long-term experiment intended to investigate how to design such collectivities. Therefore, the MICRobES robots have no prior specific functionality, they have to develop individual competences, a social organization, and sociability towards humans in order to "survive" in a dynamic environment
Using Belief Theory to Diagnose Control Knowledge Quality. Application to cartographic generalisation
Both humans and artificial systems frequently use trial and error methods to
problem solving. In order to be effective, this type of strategy implies having
high quality control knowledge to guide the quest for the optimal solution.
Unfortunately, this control knowledge is rarely perfect. Moreover, in
artificial systems-as in humans-self-evaluation of one's own knowledge is often
difficult. Yet, this self-evaluation can be very useful to manage knowledge and
to determine when to revise it. The objective of our work is to propose an
automated approach to evaluate the quality of control knowledge in artificial
systems based on a specific trial and error strategy, namely the informed tree
search strategy. Our revision approach consists in analysing the system's
execution logs, and in using the belief theory to evaluate the global quality
of the knowledge. We present a real-world industrial application in the form of
an experiment using this approach in the domain of cartographic generalisation.
Thus far, the results of using our approach have been encouraging.Comment: Best paper award, International Conference on Computing and
Communication Technologies (IEEE-RIVF), Danang : Viet Nam (2009
Des données géographiques à la simulation à base d'agents : application de la plate-forme GAMA
International audienceCes derniĂšres annĂ©es, la simulation Ă base dâagents a rĂ©vĂ©lĂ© certains intĂ©rĂȘts en gĂ©ographie. NĂ©anmoins, sâil existe aujourdâhui de nombreuses plates-formes permettant de faciliter le dĂ©veloppement de modĂšle, celles-ci sont souvent trop complexes pour ĂȘtre utilisĂ©es par des non-informaticiens (par exemple Repast Symphony) ou trop limitĂ©es pour dĂ©velopper des modĂšles riches intĂ©grant de nombreux agents et donnĂ©es (par exemple Netlogo). La plate-forme GAMA a pour objectif dâoffrir aux modĂ©lisateurs une plate-forme Ă la fois puissante et simple dâaccĂšs grĂące Ă langage de modĂ©lisation dĂ©diĂ©. Dans cet article, nous prĂ©sentons les capacitĂ©s particuliĂšrement avancĂ©es de la nouvelle version de la plate-forme GAMA pour la gestion de lâespace. Cette plate-forme permet en particulier de gĂ©rer simultanĂ©ment plusieurs environnements basĂ©s sur trois types de topologie (continue, grille, graphe), dâintĂ©grer trĂšs simplement des donnĂ©es gĂ©ographiques (vectorielles et rasters) et de reprĂ©senter des gĂ©omĂ©tries dans un environnement 3D. Les capacitĂ©s dĂ©taillĂ©es dans cet article sont illustrĂ©es par un modĂšle sur les problĂ©matiques de sĂ©grĂ©gation urbaine
An architecture for modular distributed simulation with agent-based models
Agent-based simulations are an increasingly popular means of exploring and understanding complex social systems. In order to be useful, these simulations must capture a range of aspects of the modeled situation, each possibly requiring distinct expertise. Moreover, different paradigms may be useful in modelling, ranging from those that use many lightweight reactive agents, to those that use cognitive agents, to those that focus on agent teams and organisational structures. There is need for an architecture which supports the development of a large simulation, through the integration of separately developed modules. This paper describes a framework and architecture which facilitates the integration of multiple agent-based simulations into a single global simulation. This architecture naturally supports distributed simulation and incremental development, which are ways of addressing the computational and conceptual complexity of such systems. In this paper we focus particularly on how to ensure proper management of simulation data that is affected by agents in different modules, at the same logical time. We also provide some preliminary performance evaluation addressing scalability, as well as a comparison of how other available systems handle the issue of shared data
- âŠ