Section: Research Program

Imperfect Information and Priorities

While classical FOL is the kernel of many KRR languages, to solve real-world problems we often need to consider features that cannot be expressed purely (or not naturally) in classical logic. The logic- and graph-based formalisms used for previous points have thus to be extended with such features. The following requirements have been identified from scenarios in decision making in the agronomy domain (see Section  4.2 ):

  1. to cope with vague and uncertain information and preferences in queries;

  2. to cope with multi-granularity knowledge;

  3. to take into account different and potentially conflicting viewpoints ;

  4. to integrate decision notions (priorities, gravity, risk, benefit);

  5. to integrate argumentation-based reasoning.

Although the solutions we will develop need to be validated on the applications that motivated them, we also want them to be sufficiently generic to be applied in other contexts. One angle of attack (but not the only possible one) consists in increasing the expressivity of our core languages, while trying to preserve their essential combinatorial properties, so that algorithmic optimizations can be transferred to these extensions. To achieve that goal, our main research directions are: non-monotonic reasoning (see ANR project ASPIQ in Section  8.1 ), as well as argumentation and preferences (see Section  6.2 ).