Abstract
Multistage decision transition systems (MDTSs) were proposed to describe transitions among states observed in the given systems. If we are interested in sequences of changes of states, then we may represent such changes by means of polyadic transition relations over the sets of states. A given MDTS represents such a relation. Each object in MDTS is referred to as an episode.We can extend a given MDTS by adding new episodes to it. The important question is as follows: ‘what is a consistency factor of a new episode added to MDTS with the knowledge included in MDTS?’. In the standard approach, if we wish to answer this question, then we compute the set of all minimal decision rules true in MDTS. Such a problem is NP-hard. In the paper, we present the answer to the question using a crucial notion of rough sets, namely a lower approximation of an appropriate set of episodes in MDTS. Moreover, we give some theoretical foundations of extensions of MDTS from the rough set point of view.
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Pancerz, K. (2009). Extensions of Multistage Decision Transition Systems: The Rough Set Perspective. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_21
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DOI: https://doi.org/10.1007/978-3-642-00563-3_21
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