5 citations · 9 across the 6 of their papers we have counts for
6 papers
ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning
Ignacio D. Lopez-Miguel, Andreas Happe, Jürgen Cito +3
Large Language Model (LLM)-based agents are increasingly used for complex tasks such as software testing and cybersecurity assessment. While these agents demonstrate impressive cap…
ORCAID: Oblique Rule-Based Continuous-Action Interpretation for Deep RL Policies
Ignacio D. Lopez-Miguel, Ezio Bartocci, Thomas Eiter +1
Explainability remains a key issue in reinforcement learning (RL). Distilling an interpretable policy from an agent trained in a complex environment is particularly challenging whe…
Rule-Guided Reinforcement Learning Policy Evaluation and Improvement
Martin Tappler, Ignacio D. Lopez-Miguel, Sebastian Tschiatschek +1
We consider the challenging problem of using domain knowledge to improve deep reinforcement learning policies. To this end, we propose LEGIBLE, a novel approach, following a multi-…
Formal Verification of PLCs as a Service: A CERN-GSI Safety-Critical Case Study (extended version)
Ignacio D. Lopez-Miguel, Borja Fernández Adiego, Matias Salinas +1
The increased technological complexity and demand for software reliability require organizations to formally design and verify their safety-critical programs to minimize systematic…
PLCverif: Status of a Formal Verification Tool for Programmable Logic Controller
Ignacio D. Lopez-Miguel, Jean-Charles Tournier, Borja Fernandez Adiego
Programmable Logic Controllers (PLC) are widely used for industrial automation including safety systems at CERN. The incorrect behaviour of the PLC control system logic can cause s…
Applying Model Checking to Highly-Configurable Safety Critical Software: The SPS-PPS PLC Program
Borja Fernandez Adiego, Ignacio D. Lopez-Miguel, Jean-Charles Tournier +3
An important aspect of many particle accelerators is the constant evolution and frequent configuration changes that are needed to perform the experiments they are designed for. Thi…