collaborators

13 papers

cs.AI2026

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…

cs.CR2026

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…

cs.AI2026

Semantic Partial Grounding via LLMs

Giuseppe Canonaco, Alberto Pozanco, Daniel Borrajo

Grounding is a critical step in classical planning, yet it often becomes a computational bottleneck due to the exponential growth in grounded actions and atoms as task size increas…

cs.AI2026

Counterfactual Reasoning in Automated Planning

Alberto Pozanco, Daniel Borrajo, Manuela Veloso

Automated planning traditionally assumes that all aspects of a planning task (initial state, goals, and available actions) are fully specified in advance, an approach well-suited t…

cs.AI2026

Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable

Alberto Pozanco, Marianela Morales, Pietro Totis +1

Most research in planning focuses on generating a plan to achieve a desired set of goals. However, a goal specification can also be used to encode a property that should never hold…

cs.AI2026

Planning with Minimal Disruption

Alberto Pozanco, Marianela Morales, Daniel Borrajo +1

In many planning applications, we might be interested in finding plans that minimally modify the initial state to achieve the goals. We refer to this concept as plan disruption. In…