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naum abstracts a given set of formulas into a conjunction of formulas that has a certain structure. The structure could be the functions in the abstracted formulas and/or number of conjunctions in the learnt abstraction. Dependencies: *Python packages: --oct2py --cvxopt --cvxpy --numpy *Proteus Inputs to naum: *Basis functions for the classifier *The set of formulas to be abstracted in 'dr' format (see dReal library of benchmarks for help) *Other learning parameters -- number of conjunctions in each classifier *Number of formulas to be abstracted together *Decomposition mode -- Hamming based/Bound based/etc... Output: The output from 'naum' is an abstracted representation of a given set of constraints that is simpler for an SMT solver to handle. Usage: 1. Clone the repo to a local drive 2. Navigate to naum/ and run $./configure $./configure_tmp.sh 2.Create a file with constraints in the 'dr' format 3. To abstract and solve your set of constraints from inside naum: $cd bin $Naum <dr file name> <parameters> where <parameters> -- sequence of five 0/1-s First position in parameter indicates whether to check for sat Second position is parameter indicates whether to check for unsat Third position is for Hamming Based Decompositon Fourth Position/Fifth are inactive currently -- so set to 0