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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 |
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| TTE-5506 2011-01 |
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Requirements
Final exam AND Assignment(s)
Principles and baselines related to teaching and learning
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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 |
| 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. |