Exploring Asu Cse 579 Knowledge Representation 2018 Lec19
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- Planning, prediction, postdiction.
- Intro to probability theory Bayes nets Markov nets.
- LPMLN examples LPMLN systems Representing Bayes nets in LPMLN.
- Markov Logic Applications LPMLN: Syntax and Semantics.
- reasoning about actions intro describing transition systems in ASP Monkey and Bananas.
In-Depth Information on Asu Cse 579 Knowledge Representation 2018 Lec19
Markov Logic semantics: template for markov networks MAP inference in Markov Logic Walksat/MaxWalkSAT. LPMLN to ASP Ontology RDF, RDFS. LPMLN vs. ASP vs. MLN. blocks world nondeterministic actions concurrent actions non-inertial fluents.
first-order logic: syntax, interpretation.
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