4 papers
Learning Symbolic Persistent Macro-Actions for POMDP Solving Over Time
Celeste Veronese, Daniele Meli, Alessandro Farinelli
This paper proposes an integration of temporal logical reasoning and Partially Observable Markov Decision Processes (POMDPs) to achieve interpretable decision-making under uncertai…
Depth-Constrained ASV Navigation with Deep RL and Limited Sensing
Amirhossein Zhalehmehrabi, Daniele Meli, Francesco Dal Santo +2
Autonomous Surface Vehicles (ASVs) play a crucial role in maritime operations, yet their navigation in shallow-water environments remains challenging due to dynamic disturbances an…
Monte Carlo Tree Search with Velocity Obstacles for safe and efficient motion planning in dynamic environments
Lorenzo Bonanni, Daniele Meli, Alberto Castellini +1
Online motion planning is a challenging problem for intelligent robots moving in dense environments with dynamic obstacles, e.g., crowds. In this work, we propose a novel approach…
Online inductive learning from answer sets for efficient reinforcement learning exploration
Celeste Veronese, Daniele Meli, Alessandro Farinelli
This paper presents a novel approach combining inductive logic programming with reinforcement learning to improve training performance and explainability. We exploit inductive lear…