Course Catalog 2013-2014
International

Basic Pori International Postgraduate Open University

|Degrees|     |Study blocks|     |Courses|    

Course Catalog 2013-2014

TTE-55006 Knowledge Representation and Reasoning Machines, 5 cr

Additional information

Suitable for postgraduate studies

Person responsible

Lastra Jose Martinez, Aleksandra Dvoryanchikova

Lessons

Study type P1 P2 P3 P4 Summer Implementations Lecture times and places
Lectures
Excercises


 


 
 2 h/week
 2 h/week
+2 h/week
+2 h/week


 
TTE-55006 2013-01 Wednesday 14 - 16, TC171

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.     

Instructions for students on how to achieve the learning outcomes

The grade will be calculated as: 50% final examination, and 50% 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   Yes    English  
Book   Semantic Web Services in Factory Automa   Martinez Lastra J.L., Delamer I.M.   952-15-1374-8     TUT library   Yes    Suomi  

Prerequisite relations (Requires logging in to POP)



Correspondence of content

Course Corresponds course  Description 
TTE-55006 Knowledge Representation and Reasoning Machines, 5 cr TTE-5506 Knowledge Representation and Reasoning Machines, 5 cr  

More precise information per implementation

Implementation Description Methods of instruction Implementation
TTE-55006 2013-01        

Last modified09.01.2014