8 citations · 9 across the 11 of their papers we have counts for
11 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…
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…
Planning Task Shielding: Detecting and Repairing Flaws in Planning Tasks through Turning them Unsolvable
Alberto Pozanco, Pietro Totis, Marianela Morales +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…
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…
Unveiling Interesting Insights: Monte Carlo Tree Search for Knowledge Discovery
Pietro Totis, Alberto Pozanco, Daniel Borrajo
Organizations are increasingly focused on leveraging data from their processes to gain insights and drive decision-making. However, converting this data into actionable knowledge r…
GenPlanX. Generation of Plans and Execution
Daniel Borrajo, Giuseppe Canonaco, Tomás de la Rosa +10
Classical AI Planning techniques generate sequences of actions for complex tasks. However, they lack the ability to understand planning tasks when provided using natural language.…
Projection Abstractions in Planning Under the Lenses of Abstractions for MDPs
Giuseppe Canonaco, Alberto Pozanco, Daniel Borrajo
The concept of abstraction has been independently developed both in the context of AI Planning and discounted Markov Decision Processes (MDPs). However, the way abstractions are bu…
TRIP-PAL: Travel Planning with Guarantees by Combining Large Language Models and Automated Planners
Tomas de la Rosa, Sriram Gopalakrishnan, Alberto Pozanco +2
Travel planning is a complex task that involves generating a sequence of actions related to visiting places subject to constraints and maximizing some user satisfaction criteria. T…
On the Sample Efficiency of Abstractions and Potential-Based Reward Shaping in Reinforcement Learning
Giuseppe Canonaco, Leo Ardon, Alberto Pozanco +1
The use of Potential-Based Reward Shaping (PBRS) has shown great promise in the ongoing research effort to tackle sample inefficiency in Reinforcement Learning (RL). However, choos…
Generalising Planning Environment Redesign
Alberto Pozanco, Ramon Fraga Pereira, Daniel Borrajo
In Environment Design, one interested party seeks to affect another agent's decisions by applying changes to the environment. Most research on planning environment (re)design assum…