-\JFC{Perspectives pour SDD->Promela}
-Among drawbacks of the method, one can argue that bounded delays is only
-realistic in practice for close systems.
-However, in real large scale distributed systems where bandwidth is weak,
-this restriction is too strong. In that case, one should only consider that
-matrix $s^{t}$ follows the iterations of the system, \textit{i.e.},
-for all $i$, $j$, $1 \le i \le j \le n$, we have$
-\lim\limits_{t \to \infty} s_{ij}^t = + \infty$.
-One challenge of this work should consist in weakening this constraint.
-We plan as future work to take into account other automatic approaches
-to discharge proofs notably by deductive analysis~\cite{CGK05}.
-
-\JFC{Perspective ANN}
-
-In future work we intend to enlarge the comparison between the
-learning of truly chaotic and non-chaotic behaviors. Other
-computational intelligence tools such as support vector machines will
-be investigated too, to discover which tools are the most relevant
-when facing a truly chaotic phenomenon. A comparison between learning
-rate success and prediction quality will be realized. Concrete
-consequences in biology, physics, and computer science security fields
-will then be stated.
-Ajouter lefait que le codede gray n'est pas optimal.
-On pourrait aussi travailler à établir un classement qui préserverait
-le fait que deux configurations voisines seraient représentées
-par deux entiers voisins. Par optimisation?
-
-\JFC{Perspectives pour les générateurs} : marcher ou sauter... comment on
-pourrait étendre, ce que l'on a déjà, ce qu'il reste à faire.
