This interpretation fits with the notion of agents. At a minimum, there can be some statement of preferences, perhaps in the form of rules, with an inference engine or some other reasoning mechanism to act on these preferences. If we also want to be able to operate under conditions of imprecision and uncertainty the intelligence of this agents needs to use fuzzy logic. Higher levels of intelligence include a user model or some other form of understanding and reasoning about what a user wants to do, and planning the means to achieve this goal. Finally networked agent applications add a third dimension to the picture.
Mobility is the degree to which agents themselves travel through the network.
To summarize, the combination of these three components let us have a multiagent system offering a decentralized control model that can be used in the development of the reactive navigation of the autonomous systems. In the following section we will describe the architecture we propose to address with intelligent multi-agents. Then, we will state the control systems, that is, how agents will be instantiated and how they will cooperate with each others. In the next section we will show the hardware we are using and our current agents configuration. Last, we will present some conclussions and future trends.