318 citations · 421 across the 9 of their papers we have counts for
10 papers
Competitions in AI -- Robustly Ranking Solvers Using Statistical Resampling
Chris Fawcett, Mauro Vallati, Holger H. Hoos +1
Solver competitions play a prominent role in assessing and advancing the state of the art for solving many problems in AI and beyond. Notably, in many areas of AI, competitions hav…
Planning for Learning Object Properties
Leonardo Lamanna, Luciano Serafini, Mohamadreza Faridghasemnia +4
Autonomous agents embedded in a physical environment need the ability to recognize objects and their properties from sensory data. Such a perceptual ability is often implemented by…
Goal Recognition as a Deep Learning Task: the GRNet Approach
Mattia Chiari, Alfonso E. Gerevini, Luca Putelli +2
In automated planning, recognising the goal of an agent from a trace of observations is an important task with many applications. The state-of-the-art approaches to goal recognitio…
Online Grounding of Symbolic Planning Domains in Unknown Environments
Leonardo Lamanna, Luciano Serafini, Alessandro Saetti +2
If a robotic agent wants to exploit symbolic planning techniques to achieve some goal, it must be able to properly ground an abstract planning domain in the environment in which it…
Prognosis Prediction in Covid-19 Patients from Lab Tests and X-ray Data through Randomized Decision Trees
Alfonso Emilio Gerevini, Roberto Maroldi, Matteo Olivato +2
AI and Machine Learning can offer powerful tools to help in the fight against Covid-19. In this paper we present a study and a concrete tool based on machine learning to predict th…
Novelty Messages Filtering for Multi Agent Privacy-preserving Planning
Alfonso E. Gerevini, Nir Lipovetzky, Nico Peli +3
In multi-agent planning, agents jointly compute a plan that achieves mutual goals, keeping certain information private to the individual agents. Agents' coordination is achieved th…