Minimal Disclosure in Partially Observable Markov Decision Processes

Nathalie Bertrand & Blaise Genest
For security and efficiency reasons, most systems do not give the users a full access to their information. One key specification formalism for these systems are the so called Partially Observable Markov Decision Processes (POMDP for short), which have been extensively studied in several research communities, among which AI and model-checking. In this paper we tackle the problem of the minimal information a user needs at runtime to achieve a simple goal, modeled as reaching...