[Artificial Intelligence Review]
Maddalena Zuccotto, Alberto Castellini, Davide La Torre, Lapo Mola and Alessandro Farinelli
Reinforcement learning applications in environmental sustainability: a review
Artificial Intelligence Review
[Journal of Artificial Intelligence Research (JAIR)]
Daniele Meli, Alberto Castellini, and Alessandro Farinelli
Learning logic specifications for policy guidance in POMDPs: an inductive logic programming approach
Journal of Artificial Intelligence Research (JAIR)
[22th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023)]
Giulio Mazzi, Daniele Meli, Alberto Castellini and Alessandro Farinelli
Learning Logic Specifications for Soft Policy Guidance in POMCP
22th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023)
[40th International Conference on Machine Learning (ICML)]
Alberto Castellini, Federico Bianchi, Edoardo Zorzi, Thiago D. Simão, Alessandro Farinelli and Matthijs T. J. Spaan
Scalable Safe Policy Improvement via Monte Carlo Tree Search
40th International Conference on Machine Learning (ICML)
[IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)]
Alberto Castellini, Francesco Masillo, Davide Azzalini, Francesco Amigoni and Alessandro Farinelli
Adversarial Data Augmentation for HMM-based Anomaly Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
[Artificial Intelligence]
Giulio Mazzi, Alberto Castellini and Alessandro Farinelli
Risk-aware shielding of Partially Observable Monte Carlo Planning policies
Artificial Intelligence
[3rd National Conference on Artificial Intelligence (Ital-IA 2023)]
Federico Bianchi, Davide Corsi, Luca Marzari, Daniele Meli, Francesco Trotti, Maddalena Zuccotto, Alberto Castellini and Alessandro Farinelli
Safe and Efficient Reinforcement Learning for Environmental Monitoring
Ital-IA 2023: 3rd National Conference on Artificial Intelligence
[Artificial Intelligence Review]
Daniele Meli, Hirenkumar Nakawala and Paolo Fiorini
Logic programming for deliberative robotic task planning
Artificial Intelligence Review
[arXiv]
Corsi Davide^, Marzari Luca^, Pore Ameya^, Farinelli Alessandro, Casals Alicia, Fiorini Paolo, and Dall’Alba Diego
Constrained Reinforcement Learning and Formal Verification for Safe Colonoscopy Navigation
arXiv:2303.03207
[arXiv]
Marzari Luca^, Corsi Davide^, Cicalese Ferdinando, and Farinelli Alessandro
The #DNN-Verification problem: Counting Unsafe Inputs for Deep Neural Networks
arXiv:2301.07068
[ICRA’23]
Marzari Luca^, Marchesini Enrico^, and Farinelli Alessandro
Online Safety Properties Collection and Refinement for Deep Reinforcement Learning Mapless Navigation
IEEE International Conference on Robotics and Automation (ICRA) 2023
[AAMAS’23]
Marchesini Enrico^, Marzari Luca^, Farinelli Alessandro, and Amato Christopher
Safe Deep Reinforcement Learning by Verifying Task-Level Properties
The 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2023
[TACAS’23]
Amir Guy^, Corsi Davide^, Yerushalmi Raz, Marzari Luca, Harel David, Farinelli Alessandro, and Katz Guy
Verifying Learning-Based Robotic Navigation Systems
Proc. 29th Int. Conf. on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) 2023
[ICRA’22]
Eleonora Tagliabue, Daniele Meli, Diego Dall’alba and Paolo Fiorini
Deliberation in autonomous robotic surgery: a framework for handling anatomical uncertainty
IEEE International Conference on Robotics and Automation (ICRA)
[CEUR Workshop Proceedings]
Daniele Meli, Giulio Mazzi, Alberto Castellini and Alessandro Farinelli
From POMDP executions to policy specifications
CEUR Workshop Proceedings
[AAAI ‘22]
Enrico Marchesini^, Davide Corsi^ and Alessandro Farinelli.
Exploring Safer Behaviors for Deep Reinforcement Learning
The 36th AAAI Conference on Artificial Intelligence (AAAI 2022)
[IEEE RTSI 2022]
Martina Capuzzo, Andrea Zanella, Maddalena Zuccotto, Federico Cunico, Marco Cristani, Alberto Castellini, Alessandro Farinelli, Luciano Gamberini.
IoT Systems for Healthy and Safe Life Environments
7th IEEE Forum on Research and Technologies for Society and Industry Innovation, RTSI (2022)
[Frontiers in Robotics and AI 2022]
Maddalena Zuccotto, Marco Piccinelli, Alberto Castellini, Enrico Marchesini and Alessandro Farinelli.
Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots
Frontiers in Robotics and AI (2022)
[SAC IRMAS ‘22]
Maddalena Zuccotto, Alberto Castellini, Alessandro Farinelli.
Learning state-variable relationships for improving POMCP performance
37th ACM/SIGAPP Symposium on Applied Computing Proceedings (SAC IRMAS) 2022
[AIxIA ‘22]
Federico Bianchi, Lorenzo Bonanni, Alberto Castellini, Alessandro Farinelli
Monte Carlo Tree Search Planning for continuous action and state spaces
The 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022)
[Applied Intelligence]
Alberto Castellini, Federico Bianchi, Alessandro Farinelli
Generation and interpretation of parsimonious predictive models for load forecasting in smart heating networks
Applied Intelligence
[SAC IRMAS ‘22]
Marzari Luca, Corsi Davide, Marchesini Enrico, and Farinelli Alessandro
Curriculum Learning for Safe Mapless Navigation
37th ACM/SIGAPP Symposium on Applied Computing Proceedings (SAC IRMAS) 2022
[Journal of Intelligent and Robotic Systems: Theory and Applications]
Michele Ginesi, Daniele Meli, Andrea Roberti, Nicola Sansonetto and Paolo Fiorini
Dynamic Movement Primitives: Volumetric Obstacle Avoidance Using Dynamic Potential Functions
Journal of Intelligent and Robotic Systems: Theory and Applications
[Machine Learning]
Daniele Meli, M. Sridharan and Paolo Fiorini
Inductive learning of answer set programs for autonomous surgical task planning: Application to a training task for surgeons
Machine Learning
[RA-L’21]
Daniele Meli and Paolo Fiorini
Unsupervised Identification of Surgical Robotic Actions from Small Homogeneous Datasets
IEEE Robotics and Automation Letters
[IROS ‘21]
Davide Corsi^, Enrico Marchesini^ and Alessandro Farinelli
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation
The 2021 International Conference on Intelligent Robots and Systems (IROS 2021)
[IROS ‘21]
Ameya Pore^, Davide Corsi^, Enrico Marchesini^, Diego Dall’Alba, Alicia Casals, Alessandro Farinelli and Paolo Fiorini
Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery
The 2021 International Conference on Intelligent Robots and Systems (IROS 2021)
[UAI ‘21]
Davide Corsi^, Enrico Marchesini^ and Alessandro Farinelli
Formal Verification of Neural Networks for Safety-Critical Tasks in Deep Reinforcement Learning
The 37th Conference on Uncertainty in Artificial Intelligence (UAI).
[ICLR ‘21]
Enrico Marchesini, Davide Corsi and Alessandro Farinelli.
Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning
The 9th International Conference on Learning Representations (ICLR)
[AIRO@AIxIA ‘21]
Maddalena Zuccotto, Alberto Castellini, Marco Piccinelli, Enrico Marchesini and Alessandro Farinelli
Learning environment properties in Partially Observable Monte Carlo Planning
AIRO@AIxIA (2021)
[IEEE ICAR ‘21]
Marzari Luca, Pore Ameya, Dall’Alba Diego, Aragon-Camarasa Gerardo, Farinelli Alessandro, and Fiorini Paolo
Towards Hierarchical Task Decomposition using Deep Reinforcement Learning for Pick and Place Subtasks
20th IEEE International Conference on Advanced Robotics (ICAR) 2021
[EAAI ‘20]
Maddalena Zuccotto, Alberto Castellini, Marco Piccinelli, Enrico Marchesini and Alessandro Farinelli
Time series segmentation for state-model generation of autonomous aquatic drones: A systematic framework
Engineering Applications of Artificial Intelligence (EAAI) 2020