Course Catalog 2011-2012
Basic

Basic Pori International Postgraduate Open University

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Course Catalog 2011-2012

TTE-5506 Knowledge Representation and Reasoning Machines, 5 cr

Additional information

Suitable for postgraduate studies

Person responsible

Lastra Jose Martinez, Aleksandra Dvoryanchikova

Lessons

Study type Hours Time span Implementations Lecture times and places
Lectures
Excercises
Assignment
2 + 2 h/week
6 h/time span
60 h/time span
13.02.2012 - 13.05.2012
13.02.2012 - 13.05.2012
13.02.2012 - 13.05.2012
TTE-5506 2011-01 Wednesday 14 - 16, RL202

Requirements

Final exam AND Assignment(s)

Principles and baselines related to teaching and learning

-

Learning outcomes

This course provides an in-depth look at different knowledge representation languages and their application to intelligent manufacturing systems. The course will explore how reasoning machines are able to collaborate and automatically reconfigure to meet evolving production needs and achieve rapid product changeover. This is the basis for creating Rapidly Reconfigurable Manufacturing Systems (RRMS). Considering knowledge as the fundamental premise for attaining intelligence, the course will cover different automatic reasoning mechanisms based on logics and inference. After the course, student should be able to capture and model the knowledge in the given problem domain. The student must understand the principles of reasoning. S/he should be able to construct basic queries on knowledge models.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Knowledge Representation Languages: First-Order Logic, Horn rules, production rules, Description Logics and Semantic Web Ontology Language (OWL), Concrete Domains and Description Logic Programming.     
2. Reasoning: Resolution, Classification and Subsumption.     
3. Knowledge Domains and Ontologies: manufacturing processes, machine skills, process and skill composition, introduction to situation calculus, product state and world state evolution.     

Evaluation criteria for the course

The grade will be calculated as: 40% final examination, and 60% course exercise works.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Study material

Type Name Author ISBN URL Edition, availability, ... Examination material Language
Book   Domain Ontologies and Reasoning Machines in Factory Automation   Martinez Lastra, J.L., Delamer, I.M., Ubis Lopez, F.   952-15-1522-8     TUT library      English  
Book   Semantic Web Services in Factory Automa   Martinez Lastra J.L., Delamer I.M.   952-15-1374-8     TUT library      Suomi  

Prerequisite relations (Requires logging in to POP)

Correspondence of content

There is no equivalence with any other courses

More precise information per implementation

Implementation Description Methods of instruction Implementation
TTE-5506 2011-01 Objectives: This course provides an in-depth look at different knowledge representation languages and their application to intelligent manufacturing systems. The course will explore how reasoning machines are able to collaborate and automatically reconfigure to meet evolving production needs and achieve rapid product changeover. This is the basis for creating Rapidly Reconfigurable Manufacturing Systems (RRMS). Considering knowledge as the fundamental premise for attaining intelligence, the course will cover different automatic reasoning mechanisms based on logics and inference.        

Last modified18.03.2011