Print Email Facebook Twitter An empirical comparison of various representations of Dynamic Systems Title An empirical comparison of various representations of Dynamic Systems Author Sun, F. Contributor Rothkrantz, L.J.M. (mentor) Faculty Electrical Engineering, Mathematics and Computer Science Department Media and knowledge engineering Programme Media and knowledge engineering Date 2010-12-16 Abstract There exist several formalisms for representation and reasoning in dynamic systems, for example, Dynamic Influence Diagrams (DID), Influence Diagrams (ID), Dynamic Bayesian Networks (DBN), Bayesian Networks (BN), Hidden Markov Models (HMM), Markov Decision Processes (MDP), and Partially Observable Markov Decision Processes (POMDP). All these formalisms belong to graphical models based on probability theory. It has been shown that all probability models can be seen as variants of one generalization model. The purpose of this thesis is to review these models, to try to propose a unifying representation of these models at some generalization level (assuming DID level), and to test them in practice. To reference this document use: http://resolver.tudelft.nl/uuid:57240194-fa7b-49af-ab5b-093919187b48 Part of collection Student theses Document type master thesis Rights (c) 2010 Sun, F. Files PDF thesis-sun.pdf 1.02 MB Close viewer /islandora/object/uuid:57240194-fa7b-49af-ab5b-093919187b48/datastream/OBJ/view