Abstract. Modern animation packages provide partial automation of action between key frames. However the creation of scenes involving many interacting characters still requires most of the work to be hand-done by animators and any automatic behavior in the animation sequence tends to be hard-wired and lacking autonomy. This paper describes our "FreeWill" prototype which addresses these limitations by proposing and implementing an extendable cognitive architecture designed to accommodate goals, actions and knowledge, thus endowing animated characters with some degree of autonomous intelligent behavior.

Scientific data are often annotated based on their properties, which are not maintained during further data processing. Not maintaining annotations results in loss of information. Decisions made on such incomplete information may be wrong. In this paper the problem of propagating annotations along a data processing chain is formulated. In particular, an annotation of a data element is an identification that this data element exhibits a specific property. The propagation of this property from the input of an operation to its output is called the identification problem. In this paper the identification problem is described as a clustering problem.

To facilitate the sharing and re-use of data in scientific studies we propose an automated technique for annotating operation results. The annotated output has to preserve, as much as possible, the properties of the input annotations. The preservation of properties is achieved by taking into account operation properties. Property preservation is evaluated with information theory metrics.