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

Training agents to follow arbitrary instructions is an important goal of multi-task reinforcement learning (RL). Linear temporal logic (LTL) provides a precise and structured formalism for specifying instructions to agents, and has been successfully adopted for training generalist multi-task policies. However, differen...

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