2021 AAAI AAAI 2021

SMT-based Safety Checking of Parameterized Multi-Agent Systems

Abstract

Abstract We study the problem of verifying whether a given parameterized multi-agent system (PMAS) is safe, namely whether none of its possible executions can lead to bad states. These are captured by a state formula existentially quantifying over agents. As the MAS is parameterized, it only describes the finite set of possible agent templates, while the actual number of concrete agent instances that will be present at runtime, for each template, is unbounded and cannot be foreseen. We solve this problem via infinite-state model checking based on satisfiability modulo theories (SMT), relying on the theory of array-based systems. We formally characterize the soundness, completeness and termination guarantees of our approach under specific assumptions. This gives us a technique that is implementable on top of third-party, SMT-based model checkers. Finally, we discuss how this approach lends itself to richer parameterized and data-aware MAS settings beyond the state-of-the-art solutions in the literature.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science and Knowledge & Reasoning
🧭 Keyword Pioneer — parameterized multi-agent system
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio