2 citations · 2 across the 9 of their papers we have counts for
9 papers
Cycle-Consistent Neural Explanation of Formal Verification Certificates
Andoni Rodriguez, Alberto Pozanco, Daniel Borrajo
Formal verification produces machine-checkable certificates that attest to the satisfaction or violation of temporal properties, yet these certificates remain opaque to non-special…
Is Your Agent Playing Dead? Deployed LLM Agents Exhibit Constraint-Evasive Fabrication and Thanatosis
Andoni Rodríguez, Alberto Pozanco, Daniel Borrajo
This paper presents and characterizes a spectrum of previously unreported behaviours we term Constraint-Evasive Fabrication (CEF): when an LLM agent operates under irreconcilable c…
Explanations for Unrealizability of Infinite-State Safety Shields
Andoni Rodriguez, Irfansha Shaik, Davide Corsi +2
Safe Reinforcement Learning focuses on developing optimal policies while ensuring safety. A popular method to address such task is shielding, in which a correct-by-construction saf…
Efficient Dynamic Shielding for Parametric Safety Specifications
Davide Corsi, Kaushik Mallik, Andoni Rodriguez +1
Shielding has emerged as a promising approach for ensuring safety of AI-controlled autonomous systems. The algorithmic goal is to compute a shield, which is a runtime safety enforc…
Research Vision: Multi-Agent Path Planning for Cops And Robbers Via Reactive Synthesis
William Fishell, Andoni Rodriguez, Mark Santolucito
We propose the problem of multi-agent path planning for a generalization of the classic Cops and Robbers game via reactive synthesis. Specifically, through the application of LTLt…
Realizable Continuous-Space Shields for Safe Reinforcement Learning
Kyungmin Kim, Davide Corsi, Andoni Rodriguez +5
While Deep Reinforcement Learning (DRL) has achieved remarkable success across various domains, it remains vulnerable to occasional catastrophic failures without additional safegua…
Verification-Guided Shielding for Deep Reinforcement Learning
Davide Corsi, Guy Amir, Andoni Rodriguez +3
In recent years, Deep Reinforcement Learning (DRL) has emerged as an effective approach to solving real-world tasks. However, despite their successes, DRL-based policies suffer fro…
Shield Synthesis for LTL Modulo Theories
Andoni Rodriguez, Guy Amir, Davide Corsi +2
In recent years, Machine Learning (ML) models have achieved remarkable success in various domains. However, these models also tend to demonstrate unsafe behaviors, precluding their…
Boolean Abstractions for Realizability Modulo Theories (Extended version)
Andoni Rodriguez, Cesar Sanchez
In this paper, we address the problem of the (reactive) realizability of specifications of theories richer than Booleans, including arithmetic theories. Our approach transforms the…