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Applications include load balancing models, epidemic spreading, cache replacement policies, or large-scale data centers, for which mean field approximation gives very accurate estimates of the transient or steady-state behaviors. In a series of recent papers [9, 7], a new and more accurate approximation, called the refined mean field approximation is presented. Yet, computing this new approximation can be cumbersome. The purpose of this paper is to present a tool, called rmf tool, that takes the description of a mean field model, and can numerically compute its mean field approximations and refinement.<\/jats:p>","DOI":"10.1145\/3543146.3543156","type":"journal-article","created":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T22:38:08Z","timestamp":1654555088000},"page":"35-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["rmf tool - A library to Compute (Refined) Mean Field Approximation(s)"],"prefix":"10.1145","volume":"49","author":[{"given":"Sebastian","family":"Allmeier","sequence":"first","affiliation":[{"name":"Univ. Grenoble Alpes Inria Grenoble, France"}]},{"given":"Nicolas","family":"Gast","sequence":"additional","affiliation":[{"name":"Univ. 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