3 papers
cs.LO2025
Analyzing Value Functions of States in Parametric Markov Chains
Kasper Engelen, Guillermo A. Pérez, Shrisha Rao
Parametric Markov chains (pMC) are used to model probabilistic systems with unknown or partially known probabilities. Although (universal) pMC verification for reachability propert…
cs.AI2025
The Limits of AI Explainability: An Algorithmic Information Theory Approach
Shrisha Rao
This paper establishes a theoretical foundation for understanding the fundamental limits of AI explainability through algorithmic information theory. We formalize explainability as…
cs.LO2025
Data Structures for Finite Downsets of Natural Vectors: Theory and Practice
Michaël Cadilhac, Vanessa Flügel, Guillermo A. Pérez +1
Manipulating downward-closed sets of vectors forms the basis of so-called antichain-based algorithms in verification. In that context, the dimension of the vectors is intimately ti…