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Transformation Diagramatic withoutLabelling
.+The+compression+is+permissive+to+a+lossy+case%252C+where+the+constructed+model+is+allowed+to+exhibit+behavior+outside+of+the+input+transitions%252C+thus+suggesting+a+completion+of+the+input+dynamics.%250A++The+task+of+graph+transformation+model+inference+is+naturally+highly+challenging+due+to+the+combinatorics+involved.+We+tackle+the+exponential+explosion+by+proposing+a+heuristically+minimal+translation+of+the+task+into+a+well-established+problem%252C+set+cover%252C+for+which+highly+optimized+solutions+exist.+We+further+showcase+how+our+results+relate+to+Kolmogorov+complexity+expressed+in+terms+of+graph+transformation.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.c4cb92037e6a72da786803b2417957ad%3frik%3dfr64E7zhDE4rYQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Transformation+Diagramatic+without+Labelling&simid=608049073947020380&FORM=IRPRST&ck=92965752CE4177D41C5C19707172435D&selectedIndex=23&itb=0)
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