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Course Catalog 2010-2011
MAT-42106 Applied logics, 5 cr |
Person responsible
Esko Turunen
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Examination or partial examinations.
Completion parts must belong to the same implementation
Principles and baselines related to teaching and learning
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Learning outcomes
The student will know the aim and principles of (1) data mining, in particular to the GUHA-method and its applications and (2) mathematical foundations and (3) applications of various non-classical logics.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Introduction to data mining; does my data contain something interesting I did not know? The GUHA method: data matrices as finite models, 'almost all', 'in most cases', 'above average' and other non-standard quantifiers. | Introduction to LISpMiner, a software implementation of the GUHA method. Practical data mining tasks by LISp Miner. | |
| 2. | Introduction to mathematical fuzzy logic; real life situations where neither black-or-white logic nor statistical methods are applicable. | Graded similarity as a base of fuzzy reasoning. Fuzzy IF-THEN rules. Constructing real world applications by means of multiple valued logic. Para consistent logic in solving decision making problems. | |
| 3. | Monoidal Logic as a basis of various non-standard logics: linear logic, intuitionistic logic, basic fuzzy logic, Lukasiewicz logic. | Residuated lattices, Girard monoids, Heyting algebras, BL-algebras, Wajsberg algebras and MV-algebras. Semantics, syntax and completeness of various non-standard logics. |
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Book | Mathematics behind Fuzzy Logic | Esko Turunen | 3-7908-1221-8 | Springer-Verlag, 1999, ISBN 3-7908-1221-8 | English | ||
| Other online content | LISpMiner | Jan Rauch | English | ||||
| Online book | Mechanizing hypothesis formation | Hajek, P., Havranek, T. | English |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
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Additional information
It is possible to take three separate parts of the course, each to the extent of 2 credits. However, only the largest extent of the course can be included in a M. Sc. or PhD. degree. In case there are several entries of different implementation rounds the credits of independent parts will be summed up.
Suitable for postgraduate studies
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
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Contact teaching: 35 % Distance learning: 0 % Self-directed learning: 65 % |