the obstacle. This can be achieved by letting the obstacle finder send the plan for avoiding, using the internal action `tellHow`.

This case study shows that the agents are able to cooperate and that messaging is actually working quite efficiently. It must be noted that information in the message should be reacted to immediately after reception, so in other examples, where fast reaction to messages is necessary, results may not be as promising.

Future thoughts
===============

As was shown in the case studies, the system is able to map ${A_{\textsf{Jason}}}$ to ${A_{\textsf{Lego}}}$. This means that given an implementation of a system in *Jason*, a group of Lego robots would be able to act as the agents implemented in *Jason*. However, some parts of the system are not as efficient as they could be, and there are still plenty of possibilities for extending the system further. In the following I will discuss some of these issues and possibilities.

#### Performance

It was shown that performance is not optimal, since in order to give ${A_{\textsf{Jason}}}$ enough time to react on a percept sent by ${A_{\textsf{Lego}}}$, the latter is forced to act very slowly. In order to make the system really useful, it 