Author

Alessandro Farinelli

View on Semantic Scholar

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Jul 2026

Explaining Reinforcement Learning Agents via Inductive Logic Programming

This work employs Inductive Logic Programming (ILP) to extract symbolic representations of RL policies and define a novel set of explainability metrics, including activation rate, feature coverage, syntactic distance and semantic distance, which provide crucial insights for the transfer and generalization of action-specific policies.

Celeste Veronese, Edoardo Zorzi, Daniele Meli et al. · 0 citations

Conference Open access Jul 2026

Symbolic Knowledge Transfer for Sample-Efficient Deep Reinforcement Learning

This work proposes a neuro-symbolic DRL approach that incorporates background symbolic knowledge to improve both sample efficiency and generalization to more challenging, unseen tasks and demonstrates consistent performance improvements over a state-of-the-art reward machine baseline.

Celeste Veronese, Alessandro Farinelli, Daniele Meli · Proceedings of the TwentyThi... · 0 citations