On-line semantic mapping. - Emanuele Bastianelli; Domenico Daniele Bloisi; Roberto Capobianco; F. Cossu; Guglielmo Gemignani; Luca Iocchi; Daniele Nardi (ICAR, 2013)

Knowledge Representation for Robots through Human-Robot Interaction. - Emanuele Bastianelli; Domenico Bloisi; Roberto Capobianco; Guglielmo Gemignani; Luca Iocchi; Daniele Nardi (CoRR, 2013)

Robust and Incremental Robot Learning by Imitation. - Roberto Capobianco (DWAI@AI*IA, 2014)

Automatic Extraction of Structural Representations of Environments. - Roberto Capobianco; Guglielmo Gemignani; Domenico Daniele Bloisi; Daniele Nardi; Luca Iocchi (IAS, 2014)

Interactive Semantic Mapping: Experimental Evaluation. - Guglielmo Gemignani; Daniele Nardi; Domenico Daniele Bloisi; Roberto Capobianco; Luca Iocchi (ISER, 2014)

Approaching Qualitative Spatial Reasoning About Distances and Directions in Robotics. - Guglielmo Gemignani; Roberto Capobianco; Daniele Nardi (AI*IA, 2015)

A proposal for semantic map representation and evaluation. - Roberto Capobianco; Jacopo Serafin; Johann Dichtl; Giorgio Grisetti; Luca Iocchi; Daniele Nardi (ECMR, 2015)

Contexts for Symbiotic Autonomy: Semantic Mapping, Task Teaching and Social Robotics. - Roberto Capobianco; Guglielmo Gemignani; Luca Iocchi; Daniele Nardi; Francesco Riccio; Andrea Vanzo (AAAI Workshop: Symbiotic Cognitive Systems, 2016)

Learning human-robot handovers through π-STAM: Policy improvement with spatio-temporal affordance maps. - Francesco Riccio; Roberto Capobianco; Daniele Nardi (Humanoids, 2016)

Improved Learning of Dynamics Models for Control. - Arun Venkatraman; Roberto Capobianco; Lerrel Pinto; Martial Hebert; Daniele Nardi; J. Andrew Bagnell (ISER, 2016)

STAM: A Framework for Spatio-Temporal Affordance Maps. - Francesco Riccio; Roberto Capobianco; Marc Hanheide; Daniele Nardi (MESAS, 2016)

Using Monte Carlo Search with Data Aggregation to Improve Robot Soccer Policies. - Francesco Riccio; Roberto Capobianco; Daniele Nardi (RoboCup, 2016)

Learning to Smooth with Bidirectional Predictive State Inference Machines. - Wen Sun 002; Roberto Capobianco; Geoffrey J. Gordon; J. Andrew Bagnell; Byron Boots (UAI, 2016)

Living with robots: Interactive environmental knowledge acquisition. - Guglielmo Gemignani; Roberto Capobianco; Emanuele Bastianelli; Domenico Daniele Bloisi; Luca Iocchi; Daniele Nardi (Robotics Auton. Syst., 2016)

Interactive generation and learning of semantic-driven robot behaviors. - Roberto Capobianco (2017)

DOP: Deep Optimistic Planning with Approximate Value Function Evaluation. - Francesco Riccio; Roberto Capobianco; Daniele Nardi (AAMAS, 2018)

HI-VAL: Iterative Learning of Hierarchical Value Functions for Policy Generation. - Roberto Capobianco; Francesco Riccio; Daniele Nardi (IAS, 2018)

Q-CP: Learning Action Values for Cooperative Planning. - Francesco Riccio; Roberto Capobianco; Daniele Nardi (ICRA, 2018)

Efficient Long-term Mapping in Dynamic Environments. - Maria Teresa Lazaro; Roberto Capobianco; Giorgio Grisetti (IROS, 2018)

S-AVE: Semantic Active Vision Exploration and Mapping of Indoor Environments for Mobile Robots. - José V. Jaramillo; Roberto Capobianco; Francesco Riccio; Daniele Nardi (AIRO@AI*IA, 2019)

Cooperative Multi-Agent Deep Reinforcement Learning in Soccer Domains. - Jim Martin Catacora Ocana; Francesco Riccio; Roberto Capobianco; Daniele Nardi (AAMAS, 2019)

Cooperative Multi-agent Deep Reinforcement Learning in a 2 Versus 2 Free-Kick Task. - Jim Martin Catacora Ocana; Francesco Riccio; Roberto Capobianco; Daniele Nardi (RoboCup, 2019)

Reinforcement Learning for Optimization of COVID-19 Mitigation Policies. - Varun Raj Kompella; Roberto Capobianco; Stacy Jong; Jonathan Browne; Spencer J. Fox; Lauren Ancel Meyers; Peter R. Wurman; Peter Stone 001 (AI4SG@AAAI Fall Symposium, 2020)

GUESs: Generative modeling of Unknown Environments and Spatial Abstraction for Robots. - Francesco Riccio; Roberto Capobianco; Daniele Nardi (AAMAS, 2020)

Explainable Inference on Sequential Data via Memory-Tracking. - Biagio La Rosa; Roberto Capobianco; Daniele Nardi (IJCAI, 2020)

Tafl-ES: Exploring Evolution Strategies for Asymmetrical Board Games. - Roberto Gallotta; Roberto Capobianco (AI*IA, 2021)

Detection Accuracy for Evaluating Compositional Explanations of Units. - Sayo M. Makinwa; Biagio La Rosa; Roberto Capobianco (AI*IA, 2021)

Exploration-Intensive Distractors: Two Environment Proposals and a Benchmarking. - Jim Martin Catacora Ocana; Roberto Capobianco; Daniele Nardi (AI*IA, 2021)

A Discussion about Explainable Inference on Sequential Data via Memory-Tracking. - Biagio La Rosa; Roberto Capobianco; Daniele Nardi (DP@AI*IA, 2021)

Multiagent Epidemiologic Inference through Realtime Contact Tracing. - Guni Sharon; James Ault; Peter Stone 001; Varun Raj Kompella; Roberto Capobianco (AAMAS, 2021)

Autonomous Planetary Landing via Deep Reinforcement Learning and Transfer Learning. - Giulia Ciabatti; Shreyansh Daftry; Roberto Capobianco (CVPR Workshops, 2021)

Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models. - Biagio La Rosa; Roberto Capobianco; Daniele Nardi (CoRR, 2021)

Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies. - Roberto Capobianco; Varun Raj Kompella; James Ault; Guni Sharon; Stacy Jong; Spencer J. Fox; Lauren Ancel Meyers; Peter R. Wurman; Peter Stone 001 (J. Artif. Intell. Res., 2021)

LoOP: Iterative learning for optimistic planning on robots. - Francesco Riccio; Roberto Capobianco; Daniele Nardi (Robotics Auton. Syst., 2021)

Grounding LTLf Specifications in Images. - Elena Umili; Roberto Capobianco; Giuseppe De Giacomo (NeSy, 2022)

Molecule Generation from Input-Attributions over Graph Convolutional Networks. - Dylan Savoia; Alessio Ragno; Roberto Capobianco (CoRR, 2022)

Semi-Supervised GCN for learning Molecular Structure-Activity Relationships. - Alessio Ragno; Dylan Savoia; Roberto Capobianco (CoRR, 2022)

Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal. - Eleonora Proia; Alessio Ragno; Lorenzo Antonini; Manuela Sabatino; Milan Mladenovic; Roberto Capobianco; Rino Ragno (J. Comput. Aided Mol. Des., 2022)

Outracing champion Gran Turismo drivers with deep reinforcement learning. - Peter R. Wurman; Samuel Barrett; Kenta Kawamoto; James MacGlashan; Kaushik Subramanian; Thomas J. Walsh 001; Roberto Capobianco; Alisa Devlic; Franziska Eckert; Florian Fuchs 004; Leilani Gilpin; Piyush Khandelwal; et al. (Nat., 2022)

Understanding Deep RL Agent Decisions: a Novel Interpretable Approach with Trainable Prototypes. - Caterina Borzillo; Alessio Ragno; Roberto Capobianco (XAI.it@AI*IA, 2023)

Grounding LTLf Specifications in Image Sequences. - Elena Umili; Roberto Capobianco; Giuseppe De Giacomo (KR, 2023)

Memory Replay For Continual Learning With Spiking Neural Networks. - Michela Proietti; Alessio Ragno; Roberto Capobianco (MLSP, 2023)

Visual Reward Machines. - Elena Umili; Francesco Argenziano; Aymeric Barbin; Roberto Capobianco (NeSy, 2023)

Towards a fuller understanding of neurons with Clustered Compositional Explanations. - Biagio La Rosa; Leilani Gilpin; Roberto Capobianco (NeurIPS, 2023)

An Overview of Environmental Features that Impact Deep Reinforcement Learning in Sparse-Reward Domains. - Jim Martin Catacora Ocana; Roberto Capobianco; Daniele Nardi (J. Artif. Intell. Res., 2023)

State of the Art of Visual Analytics for eXplainable Deep Learning. - Biagio La Rosa; Graziano Blasilli; Romain Bourqui; David Auber; Giuseppe Santucci; Roberto Capobianco; Enrico Bertini; Romain Giot; Marco Angelini (Comput. Graph. Forum, 2023)

Editorial: Ethical design of artificial intelligence-based systems for decision making. - Giulio Biondi; Stefano Cagnoni; Roberto Capobianco; Valentina Franzoni; Francesca A. Lisi; Alfredo Milani; Jordi Vallverdú (Frontiers Artif. Intell., 2023)

A self-interpretable module for deep image classification on small data. - Biagio La Rosa; Roberto Capobianco; Daniele Nardi (Appl. Intell., 2023)

Transfer Learning between non-Markovian RL Tasks through Semantic Representations of Temporal States. - Andrea Fanti 001; Elena Umili; Roberto Capobianco (AAPEI@ECAI, 2024)

Real-Time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing. - Catherine Weaver; Roberto Capobianco; Peter R. Wurman; Peter Stone 001; Masayoshi Tomizuka (ACC, 2024)

Transparent Explainable Logic Layers. - Alessio Ragno; Marc Plantevit; Céline Robardet; Roberto Capobianco (ECAI, 2024)

Neural Reward Machines. - Elena Umili; Francesco Argenziano; Roberto Capobianco (ECAI, 2024)

DeepDFA: Automata Learning through Neural Probabilistic Relaxations. - Elena Umili; Roberto Capobianco (ECAI, 2024)

Identifying Candidates for Protein-Protein Interaction: A Focus on NKp46's Ligands. - Alessia Borghini; Federico Di Valerio; Alessio Ragno; Roberto Capobianco (EXPLIMED@ECAI, 2024)

Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening. - Michela Proietti; Alessio Ragno; Biagio La Rosa; Rino Ragno; Roberto Capobianco (Mach. Learn., 2024)

Prototype-Based Interpretable Graph Neural Networks. - Alessio Ragno; Biagio La Rosa; Roberto Capobianco (IEEE Trans. Artif. Intell., 2024)

IMPO: Interpretable Memory-based Prototypical Pooling. - Alessio Ragno; Roberto Capobianco (WSDM, 2025)