Abstract
Rough mereology is a paradigm allowing for approximate reasoning in data oriented approach. It is rooted in Rough Set Theory [4]. Rough sets and rough mereology have been applied in particular to problems of formal language and grammar theories [2], [3] by Păun, Polkowski and Skowron and to problems of synthesis of grammars from data about multi-agent systems [8]. Here, we continue the topic of [8] on a meta-level: we introduce rough mereological distances (similarity measures) not only on granules of knowledge but also on pairs of granules (i.e. on decision rules) as well as on collections of pairs (i.e. on decision algorithms). This will provide a tool for extending the construction of synthesis grammars proposed in [8] in terms of granules to synthesis grammars defined in terms of decision algorithms.
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