Policy gradient approaches for multi-objective sequential decision making: A comparison. - Simone Parisi; Matteo Pirotta; Nicola Smacchia; Luca Bascetta; Marcello Restelli (ADPRL, 2014)

Policy gradient approaches for multi-objective sequential decision making. - Simone Parisi; Matteo Pirotta; Nicola Smacchia; Luca Bascetta; Marcello Restelli (IJCNN, 2014)

Multi-Objective Reinforcement Learning with Continuous Pareto Frontier Approximation. - Matteo Pirotta; Simone Parisi; Marcello Restelli (AAAI, 2015)

Reinforcement learning vs human programming in tetherball robot games. - Simone Parisi; Hany Abdulsamad; Alexandros Paraschos; Christian Daniel; Jan Peters 001 (IROS, 2015)

Local-utopia policy selection for multi-objective reinforcement learning. - Simone Parisi; Alexander Blank; Tobias Viernickel; Jan Peters 001 (SSCI, 2016)

Multi-objective Reinforcement Learning through Continuous Pareto Manifold Approximation. - Simone Parisi; Matteo Pirotta; Marcello Restelli (J. Artif. Intell. Res., 2016)

Estimating Leaf Area Index (LAI) in Vineyards Using the PocketLAI Smart-App. - Francesca Orlando; Ermes Movedi; Davide Coduto; Simone Parisi; Lucio Brancadoro; Valentina Pagani; Tommaso Guarneri; Roberto Confalonieri 002 (Sensors, 2016)

Policy Search with High-Dimensional Context Variables. - Voot Tangkaratt; Herke van Hoof; Simone Parisi; Gerhard Neumann; Jan Peters 001; Masashi Sugiyama (AAAI, 2017)

Goal-driven dimensionality reduction for reinforcement learning. - Simone Parisi; Simon Ramstedt; Jan Peters 001 (IROS, 2017)

Manifold-based multi-objective policy search with sample reuse. - Simone Parisi; Matteo Pirotta; Jan Peters 001 (Neurocomputing, 2017)

TD-regularized actor-critic methods. - Simone Parisi; Voot Tangkaratt; Jan Peters 001; Mohammad Emtiyaz Khan (Mach. Learn., 2019)

Accuracy Evaluation and Clinical Application of an Optimized Solution for Measuring Spatio-Temporal Gait Parameters. - Ilaria Mileti; Juri Taborri; Livio D'Alvia; Simone Parisi; Maria Chiara Ditto; Clara Lisa Peroni; Marco Scarati; Marta Priora; Stefano Rossi; Enrico Fusaro; Zaccaria Del Prete; Eduardo Palermo (MeMeA, 2020)

Reinforcement Learning with Sparse and Multiple Rewards. - Simone Parisi (2020)

Interesting Object, Curious Agent: Learning Task-Agnostic Exploration. - Simone Parisi; Victoria Dean; Deepak Pathak; Abhinav Gupta 001 (NeurIPS, 2021)

The Unsurprising Effectiveness of Pre-Trained Vision Models for Control. - Simone Parisi; Aravind Rajeswaran; Senthil Purushwalkam; Abhinav Gupta 001 (ICML, 2022)

Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. - Simone Parisi; Davide Tateo; Maximilian Hensel; Carlo D'Eramo; Jan Peters 001; Joni Pajarinen (Algorithms, 2022)

Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques. - Paolo Bertellini; Gianluca D'Addese; Giorgia Franchini; Simone Parisi; Carmelo Scribano; Daniele Zanirato; Marko Bertogna (FedCSIS, 2023)

Monitored Markov Decision Processes. - Simone Parisi; Montaser Mohammedalamen; Alireza Kazemipour; Matthew E. Taylor; Michael Bowling (AAMAS, 2024)

Beyond Optimism: Exploration With Partially Observable Rewards. - Simone Parisi; Alireza Kazemipour; Michael Bowling (NeurIPS, 2024)

Model-Based Exploration in Monitored Markov Decision Processes. - Alireza Kazemipour; Simone Parisi; Matthew E. Taylor; Michael Bowling (CoRR, 2025)

Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation. - Carmelo Scribano; Elena Govi; Paolo Bertellini; Simone Parisi; Giorgia Franchini; Marko Bertogna (CoRR, 2025)