In some different research fields a research issue has been to establish if the external, observed behaviour of an entity is conformant to some rules/specifications/expectations. Research areas like Multi Agent Systems, Business Process, and Legal/Normative systems, have proposed different characterizations of the same problem, named as the conformance problem. Most of the available systems, however, provide only simple yes/no answers to the conformance issue. In this paper we introduce the idea of a gradual conformance, expressed in fuzzy terms. To this end, we present a system based on a fuzzy extension of Drools, and exploit it to perform conformance tests. In particular, we consider two aspects: the first related to fuzzy ontological aspects, and the second about fuzzy time-related aspects. Moreover, we discuss how to conjugate the fuzzy contributions from these aspects to get a single, fuzzy score representing a conformance degree.
S. Bragaglia, F. Chesani, P. Mello, M. Montali, D. Sottara (2011). Fuzzy Conformance Checking of Observed Behaviour with Expectations. BERLIN : Springer-Verlag [10.1007/978-3-642-23954-0_10].
Fuzzy Conformance Checking of Observed Behaviour with Expectations
BRAGAGLIA, STEFANO;CHESANI, FEDERICO;MELLO, PAOLA;MONTALI, MARCO;SOTTARA, DAVIDE
2011
Abstract
In some different research fields a research issue has been to establish if the external, observed behaviour of an entity is conformant to some rules/specifications/expectations. Research areas like Multi Agent Systems, Business Process, and Legal/Normative systems, have proposed different characterizations of the same problem, named as the conformance problem. Most of the available systems, however, provide only simple yes/no answers to the conformance issue. In this paper we introduce the idea of a gradual conformance, expressed in fuzzy terms. To this end, we present a system based on a fuzzy extension of Drools, and exploit it to perform conformance tests. In particular, we consider two aspects: the first related to fuzzy ontological aspects, and the second about fuzzy time-related aspects. Moreover, we discuss how to conjugate the fuzzy contributions from these aspects to get a single, fuzzy score representing a conformance degree.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.