Search for dissertations about: "probabilistic reasoning"
Showing result 1 - 5 of 23 swedish dissertations containing the words probabilistic reasoning.
-
1. Exploring Probabilistic Reasoning : A Study of How Students Contextualise Compound Chance Encounters in Explorative Settings
Abstract : This thesis aims at exploring how probabilistic reasoning arises in explorative learning situations that are random in nature. The focus is especially on what learners with scant experience of formal theories of probability do and can do when dealing with compound random situations in which they are offered opportunities to integrate different probabilistic lines of reasoning. READ MORE
-
2. Perspectives on Probabilistic Graphical Models
Abstract : Probabilistic graphical models provide a natural framework for the representation of complex systems and offer straightforward abstraction for the interactions within the systems. Reasoning with help of probabilistic graphical models allows us to answer inference queries with uncertainty following the framework of probability theory. READ MORE
-
3. Coincidences and Paranormal Belief
Abstract : In this thesis it is argued that coincidences play an important role in the formation of belief, including belief in the paranormal. Three papers are presented. READ MORE
-
4. An applied approach to numerically imprecise decision making
Abstract : Despite the fact that unguided decision making might lead to inefficient and nonoptimal decisions, decisions made at organizational levels seldom utilise decisionanalytical tools. Several gaps between the decision-makers and the computer baseddecision tools exist, and a main problem in managerial decision-making involves the lack of information and precise objective data, i. READ MORE
-
5. Chain Graphs : Interpretations, Expressiveness and Learning Algorithms
Abstract : Probabilistic graphical models are currently one of the most commonly used architectures for modelling and reasoning with uncertainty. The most widely used subclass of these models is directed acyclic graphs, also known as Bayesian networks, which are used in a wide range of applications both in research and industry. READ MORE