Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach

Daniele Meli, Alberto Castellini, Alessandro Farinelli

Partially Observable Markov Decision Processes (POMDPs) are a powerful framework for planning under uncertainty. They allow to model state uncertainty as a belief probability distr…