40 citations · 134 across the 31 of their papers we have counts for
3 papers · 1 filter
Approximate Model-Based Shielding for Safe Reinforcement Learning
Alexander W. Goodall, Francesco Belardinelli
Reinforcement learning (RL) has shown great potential for solving complex tasks in a variety of domains. However, applying RL to safety-critical systems in the real-world is not ea…
Do Androids Dream of Electric Fences? Safety-Aware Reinforcement Learning with Latent Shielding
Chloe He, Borja G. Leon, Francesco Belardinelli
The growing trend of fledgling reinforcement learning systems making their way into real-world applications has been accompanied by growing concerns for their safety and robustness…
Systematic Generalisation through Task Temporal Logic and Deep Reinforcement Learning
Borja G. León, Murray Shanahan, Francesco Belardinelli
This work introduces a neuro-symbolic agent that combines deep reinforcement learning (DRL) with temporal logic (TL) to achieve systematic zero-shot, i.e., never-seen-before, gener…