This article we present an intelligent and adaptive system for an autonomous motor-glider based on non-monotonic logic. Piloting is an activity with many constraints. It could have conflicting situations and an uncertain environment. When a pilot faces such kind of situations, he enters into reasoning under uncertainty. Because maybe there are rules with incomplete and contradictory informations, e.i. legislation rules, tower control orders, security rules… Despite the fact that decisions have to be taken at all times regarding different objectives. Default logic is used to find fixed points from ambiguous and conflicting informations. The model proposed here embeds a knowledge of the world based on a set of situations, objectives and actions. After computation of plausible solutions, decision-making is expressed thanks to a non-probabilistic model. On the other hand, we also study the property of resilience which allows to absorb and modify to overcome disturbances. The core of this property is based on the interaction of the possible solutions and the connectivity of its states. Including the resilience in our model allows to carry out the convergence of one or several goals. Eventually, we present some preliminary results of the implementation.
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