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Ricardo Cannizzaro

4 accepted papers

2026

Multiverse Mechanica: A Testbed for Learning Game Mechanics via Counterfactual Worlds

ICLR 2026poster

We study how generative world models trained on video games can go beyond mere reproduction of gameplay visuals to learning game mechanics—the modular rules that causally govern gameplay. We introduce a formalization of the concept of game mechanics that operationalizes mechanic-learning as a causal…

Cited by 0SourceScholar
2023

CAR-DESPOT: Causally-Informed Online POMDP Planning for Robots in Confounded Environments

IROS 2023poster

Robots operating in real-world environments must reason about possible outcomes of stochastic actions and make decisions based on partial observations of the true world state. A major challenge for making accurate and robust action predictions is the problem of confounding, which if left untreated c…

Cited by 10SourceScholar
2021

An Upper Confidence Bound for Simultaneous Exploration and Exploitation in Heterogeneous Multi-Robot Systems

ICRA 2021poster

Heterogeneous multi-robot systems are advantageous for operations in unknown environments because functionally specialised robots can gather environmental information, while others perform tasks. We de ne this decomposition as the scout–task robot architecture and show how it avoids the need to expl…

Cited by 26SourceScholar
2018

Data Ferrying with Swarming UAS in Tactical Defence Networks

ICRA 2018poster

In this paper we categorise swarming into four classes, depending on the manner in which swarm members communicate. We identify two of these classes as ready candidates for the provision of communications within tactical defence networks in which radio-frequency communications are highly contested o…

Cited by 16SourceScholar