@inproceedings{960b0561ee75498fa09e6972a16b50f6,
title = "Computing behavioral distances, compositionally",
abstract = "We propose a general definition of composition operator on Markov Decision Processes with rewards (MDPs) and identify a well behaved class of operators, called safe, that are guaranteed to be non-extensive w.r.t. the bisimilarity pseudometrics of Ferns et al. [10], which measure behavioral similarities between MDPs. For MDPs built using safe/non-extensive operators, we present the first method that exploits the structure of the system for (exactly) computing the bisimilarity distance on MDPs. Experimental results show significant improvements upon the non-compositional technique.",
keywords = "discount factor, multi-agent system, composition operator, Markov decision processes, parallel composition",
author = "Giorgio Bacci and Giovanni Bacci and Larsen, \{Kim G.\} and Radu Mardare",
year = "2013",
doi = "10.1007/978-3-642-40313-2\_9",
language = "English",
isbn = "978-3-642-40312-5",
volume = "8087",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "74--85",
editor = "Krishnendu Chatterjee and Jir{\'i} Sgall",
booktitle = "Mathematical Foundations of Computer Science 2013",
address = "Germany",
}