Intrinsically Motivated High-Level Planning for Agent Exploration

Gabriele Sartor, Angelo Oddi, Riccardo Rasconi, Vieri Giuliano Santucci

Abstract: This paper proposes a new open-ended learning framework which aims at implementing an autonomous agent using intrinsic motivations (IM) at two different levels.