5,614 research outputs found
A multi-agent system for on-the-fly web map generation and spatial conflict resolution
RĂ©sumĂ© Internet est devenu un moyen de diffusion de lâinformation gĂ©ographique par excellence. Il offre de plus en plus de services cartographiques accessibles par des milliers dâinternautes Ă travers le monde. Cependant, la qualitĂ© de ces services doit ĂȘtre amĂ©liorĂ©e, principalement en matiĂšre de personnalisation. A cette fin, il est important que la carte gĂ©nĂ©rĂ©e corresponde autant que possible aux besoins, aux prĂ©fĂ©rences et au contexte de lâutilisateur. Ce but peut ĂȘtre atteint en appliquant les transformations appropriĂ©es, en temps rĂ©el, aux objets de lâespace Ă chaque cycle de gĂ©nĂ©ration de la carte. Lâun des dĂ©fis majeurs de la gĂ©nĂ©ration dâune carte Ă la volĂ©e est la rĂ©solution des conflits spatiaux qui apparaissent entre les objets, essentiellement Ă cause de lâespace rĂ©duit des Ă©crans dâaffichage. Dans cette thĂšse, nous proposons une nouvelle approche basĂ©e sur la mise en Ćuvre dâun systĂšme multiagent pour la gĂ©nĂ©ration Ă la volĂ©e des cartes et la rĂ©solution des conflits spatiaux. Cette approche est basĂ©e sur lâutilisation de la reprĂ©sentation multiple et la gĂ©nĂ©ralisation cartographique. Elle rĂ©sout les conflits spatiaux et gĂ©nĂšre les cartes demandĂ©es selon une stratĂ©gie innovatrice : la gĂ©nĂ©ration progressive des cartes par couches dâintĂ©rĂȘt. Chaque couche dâintĂ©rĂȘt contient tous les objets ayant le mĂȘme degrĂ© dâimportance pour lâutilisateur. Ce contenu est dĂ©terminĂ© Ă la volĂ©e au dĂ©but du processus de gĂ©nĂ©ration de la carte demandĂ©e. Notre approche multiagent gĂ©nĂšre et transfĂšre cette carte suivant un mode parallĂšle. En effet, une fois une couche dâintĂ©rĂȘt gĂ©nĂ©rĂ©e, elle est transmise Ă lâutilisateur. Dans le but de rĂ©soudre les conflits spatiaux, et par la mĂȘme occasion gĂ©nĂ©rer la carte demandĂ©e, nous affectons un agent logiciel Ă chaque objet de lâespace. Les agents entrent ensuite en compĂ©tition pour lâoccupation de lâespace disponible. Cette compĂ©tition est basĂ©e sur un ensemble de prioritĂ©s qui correspondent aux diffĂ©rents degrĂ©s dâimportance des objets pour lâutilisateur. Durant la rĂ©solution des conflits, les agents prennent en considĂ©ration les besoins et les prĂ©fĂ©rences de lâutilisateur afin dâamĂ©liorer la personnalisation de la carte. Ils amĂ©liorent la lisibilitĂ© des objets importants et utilisent des symboles qui pourraient aider lâutilisateur Ă mieux comprendre lâespace gĂ©ographique. Le processus de gĂ©nĂ©ration de la carte peut ĂȘtre interrompu en tout temps par lâutilisateur lorsque les donnĂ©es dĂ©jĂ transmises rĂ©pondent Ă ses besoins. Dans ce cas, son temps dâattente est rĂ©duit, Ă©tant donnĂ© quâil nâa pas Ă attendre la gĂ©nĂ©ration du reste de la carte. Afin dâillustrer notre approche, nous lâappliquons au contexte de la cartographie sur le web ainsi quâau contexte de la cartographie mobile. Dans ces deux contextes, nous catĂ©gorisons nos donnĂ©es, qui concernent la ville de QuĂ©bec, en quatre couches dâintĂ©rĂȘt contenant les objets explicitement demandĂ©s par lâutilisateur, les objets repĂšres, le rĂ©seau routier et les objets ordinaires qui nâont aucune importance particuliĂšre pour lâutilisateur. Notre systĂšme multiagent vise Ă rĂ©soudre certains problĂšmes liĂ©s Ă la gĂ©nĂ©ration Ă la volĂ©e des cartes web. Ces problĂšmes sont les suivants : 1. Comment adapter le contenu des cartes, Ă la volĂ©e, aux besoins des utilisateurs ? 2. Comment rĂ©soudre les conflits spatiaux de maniĂšre Ă amĂ©liorer la lisibilitĂ© de la carte tout en prenant en considĂ©ration les besoins de lâutilisateur ? 3. Comment accĂ©lĂ©rer la gĂ©nĂ©ration et le transfert des donnĂ©es aux utilisateurs ? Les principales contributions de cette thĂšse sont : 1. La rĂ©solution des conflits spatiaux en utilisant les systĂšmes multiagent, la gĂ©nĂ©ralisation cartographique et la reprĂ©sentation multiple. 2. La gĂ©nĂ©ration des cartes dans un contexte web et dans un contexte mobile, Ă la volĂ©e, en utilisant les systĂšmes multiagent, la gĂ©nĂ©ralisation cartographique et la reprĂ©sentation multiple. 3. Lâadaptation des contenus des cartes, en temps rĂ©el, aux besoins de lâutilisateur Ă la source (durant la premiĂšre gĂ©nĂ©ration de la carte). 4. Une nouvelle modĂ©lisation de lâespace gĂ©ographique basĂ©e sur une architecture multi-couches du systĂšme multiagent. 5. Une approche de gĂ©nĂ©ration progressive des cartes basĂ©e sur les couches dâintĂ©rĂȘt. 6. La gĂ©nĂ©ration et le transfert, en parallĂšle, des cartes aux utilisateurs, dans les contextes web et mobile.Abstract Internet is a fast growing medium to get and disseminate geospatial information. It provides more and more web mapping services accessible by thousands of users worldwide. However, the quality of these services needs to be improved, especially in term of personalization. In order to increase map flexibility, it is important that the map corresponds as much as possible to the userâs needs, preferences and context. This may be possible by applying the suitable transformations, in real-time, to spatial objects at each map generation cycle. An underlying challenge of such on-the-fly map generation is to solve spatial conflicts that may appear between objects especially due to lack of space on display screens. In this dissertation, we propose a multiagent-based approach to address the problems of on-the-fly web map generation and spatial conflict resolution. The approach is based upon the use of multiple representation and cartographic generalization. It solves conflicts and generates maps according to our innovative progressive map generation by layers of interest approach. A layer of interest contains objects that have the same importance to the user. This content, which depends on the userâs needs and the mapâs context of use, is determined on-the-fly. Our multiagent-based approach generates and transfers data of the required map in parallel. As soon as a given layer of interest is generated, it is transmitted to the user. In order to generate a given map and solve spatial conflicts, we assign a software agent to every spatial object. Then, the agents compete for space occupation. This competition is driven by a set of priorities corresponding to the importance of objects for the user. During processing, agents take into account usersâ needs and preferences in order to improve the personalization of the final map. They emphasize important objects by improving their legibility and using symbols in order to help the user to better understand the geographic space. Since the user can stop the map generation process whenever he finds the required information from the amount of data already transferred, his waiting delays are reduced. In order to illustrate our approach, we apply it to the context of tourist web and mobile mapping applications. In these contexts, we propose to categorize data into four layers of interest containing: explicitly required objects, landmark objects, road network and ordinary objects which do not have any specific importance for the user. In this dissertation, our multiagent system aims at solving the following problems related to on-the-fly web mapping applications: 1. How can we adapt the contents of maps to usersâ needs on-the-fly? 2. How can we solve spatial conflicts in order to improve the legibility of maps while taking into account usersâ needs? 3. How can we speed up data generation and transfer to users? The main contributions of this thesis are: 1. The resolution of spatial conflicts using multiagent systems, cartographic generalization and multiple representation. 2. The generation of web and mobile maps, on-the-fly, using multiagent systems, cartographic generalization and multiple representation. 3. The real-time adaptation of mapsâ contents to usersâ needs at the source (during the first generation of the map). 4. A new modeling of the geographic space based upon a multi-layers multiagent system architecture. 5. A progressive map generation approach by layers of interest. 6. The generation and transfer of web and mobile maps at the same time to users
An Approach to Agent-Based Service Composition and Its Application to Mobile
This paper describes an architecture model for multiagent systems that was developed in the European project LEAP (Lightweight Extensible Agent Platform). Its main feature is a set of generic services that are implemented independently of the agents and can be installed into the agents by the application developer in a flexible way. Moreover, two applications using this architecture model are described that were also developed within the LEAP project. The application domain is the support of mobile, virtual teams for the German automobile club ADAC and for British Telecommunications
Home alone: autonomous extension and correction of spatial representations
In this paper we present an account
of the problems faced by a mobile robot given
an incomplete tour of an unknown environment,
and introduce a collection of techniques which can
generate successful behaviour even in the presence
of such problems. Underlying our approach is the
principle that an autonomous system must be motivated
to act to gather new knowledge, and to validate
and correct existing knowledge. This principle is
embodied in Dora, a mobile robot which features
the aforementioned techniques: shared representations,
non-monotonic reasoning, and goal generation
and management. To demonstrate how well this
collection of techniques work in real-world situations
we present a comprehensive analysis of the Dora
systemâs performance over multiple tours in an indoor
environment. In this analysis Dora successfully
completed 18 of 21 attempted runs, with all but
3 of these successes requiring one or more of the
integrated techniques to recover from problems
A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things
The Internet of Things (IoT) is envisioned as a global network of connected
things enabling ubiquitous machine-to-machine (M2M) communication. With
estimations of billions of sensors and devices to be connected in the coming
years, the IoT has been advocated as having a great potential to impact the way
we live, but also how we work. However, the connectivity aspect in itself only
accounts for the underlying M2M infrastructure. In order to properly support
engineering IoT systems and applications, it is key to orchestrate
heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that
the system can exhibit a goal-directed behaviour and take appropriate actions.
Yet, this form of interaction between things needs to take a user-centric
approach and by no means elude the users' requirements. To this end,
contextualisation is an important feature of the system, allowing it to infer
user activities and prompt the user with relevant information and interactions
even in the absence of intentional commands. In this work we propose a
role-based model for emergent configurations of connected systems as a means to
model, manage, and reason about IoT systems including the user's interaction
with them. We put a special focus on integrating the user perspective in order
to guide the emergent configurations such that systems goals are aligned with
the users' intentions. We discuss related scientific and technical challenges
and provide several uses cases outlining the concept of emergent
configurations.Comment: In Proceedings of the Second International Workshop on the Internet
of Agents @AAMAS201
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
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