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Lecture
Intelligent and Cognitive Systems





Learning objectives
The successful participation will provide the students with the following competences: Understanding and applying methods to simulate human problem solving habits, in particular advanced methods of symbolic and subsymbolic information processing and their application. The ability to analyse problems that are difficult to structure and shape, and to apply efficient problem solving methods. The competent application of a variety of problem solving methods for vague and uncertain information.

Content


1. Introduction


- Rationality


- Agent view


- Agent architecture




2. Advanced Problem Solving Techniques


- Problems under marginal and side conditions


- Heuristic search and metaheuristic methods


- Evolutionary algorithms


- Planning algorithms




3. Semantic Techniques


- The logic of description


- Description languages and ontology standards


- Inference systems




4. Using Uncertain/Fragmentary Knowledge


- Probabilistic inference


- Bayes networks


- Decision networks


- Sequential decision problems




5. Learning and Adaptive Systems


- Symbolic learning procedures


- Statistical learning methods


- Learning procedures for neuronic networks




6. Selected Applications





Lecturedetails





SWH3
ECTS5
Language


Hochschule Ulm
89075 Ulm
infohs-ulm.de





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