A core problem in Artificial Intelligence is the modeling of human reasoning. Classic-logical approaches are too rigid for this task, as deductive inference yielding logically correct results is not appropriate in situations where conclusions must be drawn based on the incomplet…
Part 1. Introducing probabilistic programming. 1. Probabilistic programming in a nutshell -- 2. A quick Figaro tutorial -- 3. Creating a probabilistic programming application -- 4. Probabilistic models and probabilistic programs -- 5. Modeling dependencies with Bayesian and Mark…
by Olken, Frank, Palmirani, Monica, Sottara, Davide, RuleML, Barcelona; Fort Lauderdale, Fla, International Symposium on Rules: Research-Based and Industry-Focused, Ft. Lauderdale, Fla.), RuleML, Ft. Lauderdale, Fla.)
fromLecture Notes in Computer Science
by Liu, Weiru, ECSQARU, Belfast, European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Belfast)
fromLecture Notes in Computer Science
