Edoardo Zorzi — accepted AI-conference papers

2025

Collaborative Instance Object Navigation: Leveraging Uncertainty-Awareness to Minimize Human-Agent Dialogues

Francesco Taioli, Edoardo Zorzi, Gianni Franchi, Alberto Castellini, Alessandro Farinelli, Marco Cristani +1

ICCV 2025poster

Language-driven instance object navigation assumes that a human initiates the task by providing a detailed description of the target to the embodied agent. While this description is crucial for distinguishing the target from other visually similar instances, providing it prior to navigation can be d…

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2024

Scalable Safe Policy Improvement for Factored Multi-Agent MDPs

Federico Bianchi, Edoardo Zorzi, Alberto Castellini, Thiago D. Simão, Matthijs T. J. Spaan, Alessandro Farinelli

ICML 2024poster

In this work, we focus on safe policy improvement in multi-agent domains where current state-of-the-art methods cannot be effectively applied because of large state and action spaces. We consider recent results using Monte Carlo Tree Search for Safe Policy Improvement with Baseline Bootstrapping and…

Cited by 2 Source ↗PDF ↗Scholar ↗

2023

Scalable Safe Policy Improvement via Monte Carlo Tree Search

Alberto Castellini, Federico Bianchi, Edoardo Zorzi, Thiago D. Simão, Alessandro Farinelli, Matthijs T. J. Spaan

ICML 2023poster

Algorithms for safely improving policies are important to deploy reinforcement learning approaches in real-world scenarios. In this work, we propose an algorithm, called MCTS-SPIBB, that computes safe policy improvement online using a Monte Carlo Tree Search based strategy. We theoretically prove th…

Cited by 10 Source ↗PDF ↗Scholar ↗