Les systèmes d'aide à la décision (SAD) doivent permettre aux utilisateurs (décideurs) de prendre les meilleures décisions dans les meilleurs délais. Dans cette thèse, nous nous sommes intéressés aux systèmes qui reposent sur une architecture multi-agents. En effet, les systèmes multi-agents (SMA) permettent de construire des systèmes informatiques ayant recours à l'interrogation multi-critères, souvent utilisée dans les SAD. De façon plus générale, les SMA permettent de concevoir des systèmes qui sont de nature complexe. Cependant, ils n'intègrent pas la notion de contraintes temporelles qui sont souvent très fortes dans les SAD. De plus, dans ces systèmes, des résultats même partiels ou incomplets obtenus dans les temps sont souvent préférés car plus utiles pour la prise de décision que des résultats complets et précis obtenus en retard. Pour cela, les techniques ``anytime'' (raisonnement progressif) semblent une excellente solution. Dans cette thèse, nous présentons une méthode de conception d'un système multi-agent temps réel basé sur l'exploitation des techniques ``anytime''. De plus, nous prenons en compte dans notre modèle l'aspect souvent distribué des SAD.

Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for an AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of our selected anytime algorithms for an AI problem. / Address: NaN Mob. +46 - 737 - 40 19 17

Commercial computer gaming is a large growing industry, that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards because of some broad sets of problems. Some of these problems have been solved with the advent of an open real time research platform, named as ORTS. However there still exist some fundamental AI problems that require more research to be better solved for the RTS games. There also exist some AI algorithms that can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems for the RTS games. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for each AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of selected anytime algorithms for an AI problem