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TTE-5506 Knowledge Representation and Reasoning Machines, 5 cr |
Jose Martinez Lastra
No implementations
Final exam AND Assignment(s)
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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.
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. |
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 |
Course | O/R |
TTE-5016 Introduction to Robotics and Automation | Obligatory |
TTE-5036 Control in Robotics and Automation | Obligatory |
TTE-5046 Laboratory Course in Robotics and Automation | Obligatory |
TTE-5206 System Engineering in Factory Automation | Obligatory |