Alessandro Farinelli

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 158

Top Venues

Publications

Giovanni Alberto Beltrame, Carlo Combi, Alessandro Farinelli, Roberto Posenato, Giuseppe Pozzi
Ride-Sharing in Medical Transportations: Dealing with Temporal Requirements. EDBT/ICDT Workshops (2024)
Adrià Fenoy, Jacopo Zagoli, Filippo Bistaffa, Alessandro Farinelli
Attention for the Allocation of Tasks in Multi-Agent Pickup and Delivery. SAC (2024)
Luca Marzari, Francesco Leofante, Ferdinando Cicalese, Alessandro Farinelli
Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations. CoRR (2024)
Daniele Meli, Alberto Castellini, Alessandro Farinelli
Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach. J. Artif. Intell. Res. 79 (2024)
Davide Corsi, Davide Camponogara, Alessandro Farinelli
Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement Learning. CoRR (2024)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. AAAI (2024)
Davide Corsi, Guy Amir, Guy Katz, Alessandro Farinelli
Analyzing Adversarial Inputs in Deep Reinforcement Learning. CoRR (2024)
Francesco Taioli, Stefano Rosa, Alberto Castellini, Lorenzo Natale, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Yiming Wang
Mind the Error! Detection and Localization of Instruction Errors in Vision-and-Language Navigation. CoRR (2024)
Francesco Trotti, Alessandro Farinelli, Riccardo Muradore
A Markov Decision Process Approach for Decentralized UAV Formation Path Planning. ECC (2024)
Daniele Meli, Alberto Castellini, Alessandro Farinelli
Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach. CoRR (2024)
Francesco Taioli, Stefano Rosa, Alberto Castellini, Lorenzo Natale, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Yiming Wang
I2EDL: Interactive Instruction Error Detection and Localization. CoRR (2024)
Maddalena Zuccotto, Alberto Castellini, Davide La Torre, Lapo Mola, Alessandro Farinelli
Reinforcement learning applications in environmental sustainability: a review. Artif. Intell. Rev. 57 (4) (2024)
Cristian Morasso, Daniele Meli, Yann Divet, Salvatore Sessa, Alessandro Farinelli
Planning and Inverse Kinematics of Hyper-Redundant Manipulators with VO-FABRIK. CoRR (2024)
Adrià Fenoy, Filippo Bistaffa, Alessandro Farinelli
An attention model for the formation of collectives in real-world domains. Artif. Intell. 328 (2024)
Francesco Taioli, Federico Cunico, Federico Girella, Riccardo Bologna, Alessandro Farinelli, Marco Cristani
Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language. ICCV (Workshops) (2023)
Alberto Castellini, Davide Bragantini, Davide Rossignolo, Federico Segala, Alessandro Farinelli
Tabular Model Learning in Monte Carlo Tree Search. IPS-RCRA-SPIRIT@AI*IA (2023)
Federico Bianchi, Davide Corsi, Luca Marzari, Daniele Meli, Francesco Trotti, Maddalena Zuccotto, Alberto Castellini, Alessandro Farinelli
Safe and Efficient Reinforcement Learning for Environmental Monitoring. Ital-IA (2023)
Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. CoRR (2023)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Risk-aware shielding of Partially Observable Monte Carlo Planning policies. Artif. Intell. 324 (2023)
Alberto Castellini, Federico Bianchi, Edoardo Zorzi, Thiago D. Simão, Alessandro Farinelli, Matthijs T. J. Spaan
Scalable Safe Policy Improvement via Monte Carlo Tree Search. ICML (2023)
Guy Amir, Davide Corsi, Raz Yerushalmi, Luca Marzari, David Harel, Alessandro Farinelli, Guy Katz
Verifying Learning-Based Robotic Navigation Systems. TACAS (1) (2023)
Luca Marzari, Enrico Marchesini, Alessandro Farinelli
Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. CoRR (2023)
Celeste Veronese, Daniele Meli, Filippo Bistaffa, Manel Rodriguez-Soto, Alessandro Farinelli, Juan A. Rodríguez-Aguilar
Inductive Logic Programming for Transparent Alignment with Multiple Moral Values. BEWARE@AI*IA (2023)
Francesco Trotti, Alessandro Farinelli, Riccardo Muradore
An online path planner based on POMDP for UAVs. ECC (2023)
Luca Marzari, Davide Corsi, Ferdinando Cicalese, Alessandro Farinelli
The #DNN-Verification problem: Counting Unsafe Inputs for Deep Neural Networks. CoRR (2023)
Davide Corsi, Luca Marzari, Ameya Pore, Alessandro Farinelli, Alicia Casals, Paolo Fiorini, Diego Dall'Alba
Constrained Reinforcement Learning and Formal Verification for Safe Colonoscopy Navigation. CoRR (2023)
Luca Marzari, Enrico Marchesini, Alessandro Farinelli
Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. ICRA (2023)
Giulio Mazzi, Daniele Meli, Alberto Castellini, Alessandro Farinelli
Learning Logic Specifications for Soft Policy Guidance in POMCP. CoRR (2023)
Luca Marzari, Davide Corsi, Ferdinando Cicalese, Alessandro Farinelli
The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks. IJCAI (2023)
Davide Corsi, Luca Marzari, Ameya Pore, Alessandro Farinelli, Alicia Casals, Paolo Fiorini, Diego Dall'Alba
Constrained Reinforcement Learning and Formal Verification for Safe Colonoscopy Navigation. IROS (2023)
Federico Cunico, Luigi Capogrosso, Alberto Castellini, Francesco Setti, Patrik Pluchino, Filippo Zordan, Valeria Santus, Anna Spagnolli, Stefano Cordibella, Giambattista Gennari, Mauro Borgo, Alberto Sozza, Stefano Troiano, Roberto Flor, Andrea Zanella, Alessandro Farinelli, Luciano Gamberini, Marco Cristani
The Post-pandemic Effects on IoT for Safety: The Safe Place Project. DATE (2023)
Lorenzo Bonanni, Daniele Meli, Alberto Castellini, Alessandro Farinelli
Monte Carlo Planning for Mobile Robots in Large Action Spaces With Velocity Obstacles (short paper). AIRO@AI*IA (2023)
Luca Marzari, Gabriele Roncolato, Alessandro Farinelli
Scaling #DNN-Verification Tools with Efficient Bound Propagation and Parallel Computing (regular paper). AIRO@AI*IA (2023)
Alberto Castellini, Francesco Masillo, Davide Azzalini, Francesco Amigoni, Alessandro Farinelli
Adversarial Data Augmentation for HMM-Based Anomaly Detection. IEEE Trans. Pattern Anal. Mach. Intell. 45 (12) (2023)
Enrico Marchesini, Luca Marzari, Alessandro Farinelli, Christopher Amato
Safe Deep Reinforcement Learning by Verifying Task-Level Properties. AAMAS (2023)
Luca Marzari, Gabriele Roncolato, Alessandro Farinelli
Scaling #DNN-Verification Tools with Efficient Bound Propagation and Parallel Computing. CoRR (2023)
Francesco Taioli, Federico Cunico, Federico Girella, Riccardo Bologna, Alessandro Farinelli, Marco Cristani
Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language. CoRR (2023)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Ferdinando Cicalese
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. CoRR (2023)
Francesco Taioli, Francesco Giuliari, Yiming Wang, Riccardo Berra, Alberto Castellini, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Francesco Setti
Unsupervised Active Visual Search with Monte Carlo planning under Uncertain Detections. CoRR (2023)
Giulio Mazzi, Daniele Meli, Alberto Castellini, Alessandro Farinelli
Learning Logic Specifications for Soft Policy Guidance in POMCP. AAMAS (2023)
Daniele Meli, Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
From POMDP Executions to Probabilistic Axioms. OVERLAY@AI*IA (2022)
Maddalena Zuccotto, Marco Piccinelli, Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots. Frontiers Robotics AI 9 (2022)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Curriculum learning for safe mapless navigation. SAC (2022)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Active Generation of Logical Rules for POMCP Shielding. AAMAS (2022)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Exploring Safer Behaviors for Deep Reinforcement Learning. AAAI (2022)
Alberto Castellini, Federico Bianchi, Alessandro Farinelli
Generation and interpretation of parsimonious predictive models for load forecasting in smart heating networks. Appl. Intell. 52 (9) (2022)
Filippo Bistaffa, Georgios Chalkiadakis, Alessandro Farinelli
Efficient Coalition Structure Generation via Approximately Equivalent Induced Subgraph Games. IEEE Trans. Cybern. 52 (6) (2022)
Adrià Fenoy, Filippo Bistaffa, Alessandro Farinelli
An attention model for the formation of collectives in real-world domains. CoRR (2022)
Enrico Marchesini, Alessandro Farinelli
Enhancing Deep Reinforcement Learning Approaches for Multi-Robot Navigation via Single-Robot Evolutionary Policy Search. ICRA (2022)
Maddalena Zuccotto, Alberto Castellini, Alessandro Farinelli
Learning state-variable relationships for improving POMCP performance. SAC (2022)
Federico Bianchi, Lorenzo Bonanni, Alberto Castellini, Alessandro Farinelli
Monte Carlo Tree Search Planning for Continuous Action and State Spaces (short paper). AIRO@AI*IA (2022)
Alberto Castellini, Cristian Morasso, Alessandro Farinelli
HMM-based Anomaly Interpretation for Intelligent Robots in Industry 4.0 (short paper). AIRO@AI*IA (2022)
Davide Corsi, Raz Yerushalmi, Guy Amir, Alessandro Farinelli, David Harel, Guy Katz
Constrained Reinforcement Learning for Robotics via Scenario-Based Programming. CoRR (2022)
Guy Amir, Davide Corsi, Raz Yerushalmi, Luca Marzari, David Harel, Alessandro Farinelli, Guy Katz
Verifying Learning-Based Robotic Navigation Systems. CoRR (2022)
Francesco Trotti, Eros Ghignoni, Riccardo Muradore, Alessandro Farinelli
Synthesis and Monitoring of Complex Tasks for Heterogeneous Robots in an Industry 4.0 Scenario. IAS (2022)
Maddalena Zuccotto, Marco Piccinelli, Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots. Future Internet 9 (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. RTSI (2022)
Enrico Marchesini, Alessandro Farinelli
Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. IROS (2021)
Alberto Castellini, Enrico Marchesini, Alessandro Farinelli
Partially Observable Monte Carlo Planning with state variable constraints for mobile robot navigation. Eng. Appl. Artif. Intell. 104 (2021)
Luca Marzari, Ameya Pore, Diego Dall'Alba, Gerardo Aragon-Camarasa, Alessandro Farinelli, Paolo Fiorini
Towards Hierarchical Task Decomposition using Deep Reinforcement Learning for Pick and Place Subtasks. ICAR (2021)
Ameya Pore, Davide Corsi, Enrico Marchesini, Diego Dall'Alba, Alicia Casals, Alessandro Farinelli, Paolo Fiorini
Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery. IROS (2021)
Enrico Marchesini, Alessandro Farinelli
Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation. CoRR (2021)
Francesco Giuliari, Alberto Castellini, Riccardo Berra, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Francesco Setti, Yiming Wang
POMP++: Pomcp-based Active Visual Search in unknown indoor environments. IROS (2021)
Lorenzo Brigato, Riccardo Sartea, Stefano Simonazzi, Alessandro Farinelli, Luca Iocchi, Christian Napoli
Exploiting Time Dynamics for One-Class and Open-Set Anomaly Detection. ICAISC (2) (2021)
Francesco Giuliari, Alberto Castellini, Riccardo Berra, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Francesco Setti, Yiming Wang
POMP++: Pomcp-based Active Visual Search in unknown indoor environments. CoRR (2021)
Luca Marzari, Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Curriculum Learning for Safe Mapless Navigation. CoRR (2021)
Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Formal verification of neural networks for safety-critical tasks in deep reinforcement learning. UAI (2021)
Filippo Bistaffa, Christian Blum, Jesús Cerquides, Alessandro Farinelli, Juan A. Rodríguez-Aguilar
A Computational Approach to Quantify the Benefits of Ridesharing for Policy Makers and Travellers. IEEE Trans. Intell. Transp. Syst. 22 (1) (2021)
Antonello Contini, Alessandro Farinelli
Coordination approaches for multi-item pickup and delivery in logistic scenarios. Robotics Auton. Syst. 146 (2021)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Rule-based Shielding for Partially Observable Monte-Carlo Planning. CoRR (2021)
Luca Marzari, Ameya Pore, Diego Dall'Alba, Gerardo Aragon-Camarasa, Alessandro Farinelli, Paolo Fiorini
Towards Hierarchical Task Decomposition using Deep Reinforcement Learning for Pick and Place Subtasks. CoRR (2021)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: A Rule-Based Approach. AAMAS (2021)
Alberto Castellini, Federico Bianchi, Alessandro Farinelli
Predictive Model Generation for Load Forecasting in District Heating Networks. IEEE Intell. Syst. 36 (4) (2021)
Ameya Pore, Davide Corsi, Enrico Marchesini, Diego Dall'Alba, Alicia Casals, Alessandro Farinelli, Paolo Fiorini
Safe Reinforcement Learning using Formal Verification for Tissue Retraction in Autonomous Robotic-Assisted Surgery. CoRR (2021)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Rule-based Shielding for Partially Observable Monte-Carlo Planning. ICAPS (2021)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Rule-based Shield Synthesis for Partially Observable Monte Carlo Planning. OVERLAY@GandALF (2021)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. CoRR (2021)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation. IROS (2021)
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
Genetic Soft Updates for Policy Evolution in Deep Reinforcement Learning. ICLR (2021)
Maddalena Zuccotto, Alberto Castellini, Marco Piccinelli, Enrico Marchesini, Alessandro Farinelli
Learning Environment Properties in Partially Observable Monte Carlo Planning. AIRO@AI*IA (2021)
Alberto Castellini, Manuele Bicego, Francesco Masillo, Maddalena Zuccotto, Alessandro Farinelli
Time series segmentation for state-model generation of autonomous aquatic drones: A systematic framework. Eng. Appl. Artif. Intell. 90 (2020)
Davide Corsi, Enrico Marchesini, Alessandro Farinelli
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification. CoRR (2020)
Lorenzo Steccanella, Domenico Daniele Bloisi, Alberto Castellini, Alessandro Farinelli
Waterline and obstacle detection in images from low-cost autonomous boats for environmental monitoring. Robotics Auton. Syst. 124 (2020)
Riccardo Sartea, Georgios Chalkiadakis, Alessandro Farinelli, Matteo Murari
Bayesian Active Malware Analysis. AAMAS (2020)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Policy Interpretation for Partially Observable Monte-Carlo Planning: a Rule-based Approach. AIRO@AI*IA (2020)
Federico Bianchi, Francesco Masillo, Alberto Castellini, Alessandro Farinelli
XM_HeatForecast: Heating Load Forecasting in Smart District Heating Networks. LOD (1) (2020)
Federico Bianchi, Pietro Tarocco, Alberto Castellini, Alessandro Farinelli
Convolutional Neural Network and Stochastic Variational Gaussian Process for Heating Load Forecasting. LOD (1) (2020)
Yiming Wang, Francesco Giuliari, Riccardo Berra, Alberto Castellini, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Francesco Setti
POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments. BMVC (2020)
Matteo Denitto, Manuele Bicego, Alessandro Farinelli, Sebastiano Vascon, Marcello Pelillo
Biclustering with dominant sets. Pattern Recognit. 104 (2020)
Matteo Murari, Alessandro Farinelli, Riccardo Sartea
A Game of Double Agents: Repeated Stackelberg Games with Role Switch. EUMAS/AT (2020)
Enrico Marchesini, Alessandro Farinelli
Discrete Deep Reinforcement Learning for Mapless Navigation. ICRA (2020)
Davide Azzalini, Alberto Castellini, Matteo Luperto, Alessandro Farinelli, Francesco Amigoni
HMMs for Anomaly Detection in Autonomous Robots. AAMAS (2020)
Huan Vu, Samir Aknine, Sarvapali D. Ramchurn, Alessandro Farinelli
Decentralised Multi-intersection Congestion Control for Connected Autonomous Vehicles. EUMAS/AT (2020)
Yiming Wang, Francesco Giuliari, Riccardo Berra, Alberto Castellini, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, Francesco Setti
POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments. CoRR (2020)
Davide Corsi, Enrico Marchesini, Alessandro Farinelli, Paolo Fiorini
Formal Verification for Safe Deep Reinforcement Learning in Trajectory Generation. IRC (2020)
Masoume M. Raeissi, Alessandro Farinelli
Cooperative Queuing Policies for Effective Scheduling of Operator Intervention. Auton. Robots 44 (3-4) (2020)
Enrico Marchesini, Alessandro Farinelli
Genetic Deep Reinforcement Learning for Mapless Navigation. AAMAS (2020)
Riccardo Sartea, Alessandro Farinelli, Matteo Murari
SECUR-AMA: Active Malware Analysis Based on Monte Carlo Tree Search for Android Systems. Eng. Appl. Artif. Intell. 87 (2020)
Alberto Castellini, Enrico Marchesini, Giulio Mazzi, Alessandro Farinelli
Explaining the Influence of Prior Knowledge on POMCP Policies. EUMAS/AT (2020)
Giulio Mazzi, Alberto Castellini, Alessandro Farinelli
Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: a Rule-Based Approach. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alessandro Farinelli