  The aim of this paper is to present the principles and results about
case-based reasoning adapted to real- time interactive simulations, more
precisely concerning retrieval mechanisms. The article begins by introducing
the constraints involved in interactive multiagent-based simulations. The
second section pre- sents a framework stemming from case-based reasoning by
autonomous agents. Each agent uses a case base of local situations and, from
this base, it can choose an action in order to interact with other auton- omous
agents or users' avatars. We illustrate this framework with an example
dedicated to the study of dynamic situations in football. We then go on to
address the difficulties of conducting such simulations in real-time and
propose a model for case and for case base. Using generic agents and adequate
case base structure associated with a dedicated recall algorithm, we improve
retrieval performance under time pressure compared to classic CBR techniques.
We present some results relating to the performance of this solution. The
article concludes by outlining future development of our project.
