Author

Alessandro Abate

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#artificial intelligence Preprint Sep 2026

Jaxolotl: A Unified High-Performance Benchmark Suite for LTL-Based Multi-Task RL

Jaxolotl provides a modular, end-to-end JAX implementation of six representative algorithms and four environments, together with newly curated task suites and a standardised, statistically robust evaluation protocol, which enables fully JIT-compiled training and evaluation.

Mathias Jackermeier, Jacques Cloete, Alessandro Abate · 0 citations

#machine learning Preprint Sep 2026

Efficient Bayes-Adaptive Reinforcement Learning with Temporal Logic Specifications

A novel end-to-end model-based Reinforcement Learning (RL) algorithm for efficient policy synthesis under given Linear Temporal Logic (LTL) specifications in unknown environments is presented and a successful application is showcased for \textit{cautious} RL, namely to reduce the number of task violations incurred duri...

Jonathan Hau, Alessandro Abate · 0 citations