Hauptinhalt

Topinformationen

Personen

Basic methods of probabilistic reasoning

8.3273

Dozenten

Dr. rer. nat. Nico Potyka

Beschreibung

Prerequisites: Basic knowledge in computer science and math,
in particular probability theory

Classical reasoning methods are too weak for many practical applications because they cannot deal with uncertainty. Various qualitative (e.g. non-monotonic reasoning) and quantitative (e.g. fuzzy reasoning, possibilistic reasoning) extensions have been proposed to overcome these shortcomings. In this course, we will discuss probabilistic methods that build up on probability theory. For instance, probabilistic logics extend classical logics by replacing the truth values 0 and 1 with the probability interval [0,1]. Reasoning results in classical logic are well founded by the laws of probability theory. However, in order to perform probabilistic reasoning in reasonable time, we often have to make independency assumptions. Probabilistic graphical models represent the independency structure graphically and offer various reasoning and learning algorithms that can exploit this structure. While Probabilistic graphical models can deal with large problems, their logical expressiveness is rather weak. Frameworks from the field of Statistical Relational Artificial Intelligence like Markov Logic and ProbLog can offer a better tradeoff between expressiveness and efficiency.

The first part of the course will consist of lectures, where some of the main formalisms for probabilistic reasoning are introduced. This includes Bayesian and Markov networks, which are the main families of probabilistic graphical models, and propositional probabilistic logic. In particular, we will talk about the basic reasoning (variable elimination, belief propagation) and learning (parameter/structure) methods. In the second part of the course, participants will present advanced topics.

Weitere Angaben

Ort: 32/107
Zeiten: Do. 12:00 - 14:00 (wöchentlich)
Erster Termin: Donnerstag, 07.11.2019 12:00 - 14:00, Ort: 32/107
Veranstaltungsart: Seminar (Offizielle Lehrveranstaltungen)