Feb. 5, 2024, 6:42 a.m. | Franz Brau{\ss}e Zurab Khasidashvili Konstantin Korovin

cs.LG updates on arXiv.org arxiv.org

Symbolic Machine Learning Prover (SMLP) is a tool and a library for system exploration based on data samples obtained by simulating or executing the system on a number of input vectors. SMLP aims at exploring the system based on this data by taking a grey-box approach: SMLP combines statistical methods of data exploration with building and exploring machine learning models in close feedback loop with the system's response, and exploring these models by combining probabilistic and formal methods. SMLP has …

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