2017/10/22 by Stéphane Le Roux, Guillermo A. Pérez, Roux, Stephane Le +1 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Distributed systems and fault tolerance #FOS: Computer and information sciences #Formal Methods in Verification #Logic in Computer Science (cs.LO)
paper · pdf · doi:10.48550/arxiv.1710.07903
openalex publication_date 2017/10/22 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
We study the never-worse relation (NWR) for Markov decision processes with an infinite-horizon reachability objective. A state q is never worse than a state p if the maximal probability of reaching the target set of states from p is at most the same value from q, regard- less of the probabilities labelling the transitions. Extremal-probability states, end components, and essential states are all special cases of the equivalence relation induced by the NWR. Using the NWR, states in the same equivalence class can be collapsed. Then, actions leading to sub- optimal states can be removed. We show the natural decision problem associated to computing the NWR is coNP-complete. Finally, we ex- tend a previously known incomplete polynomial-time iterative algorithm to under-approximate the NWR.