T. D. Gedeon

24400830200

Publications - 16

Motion control and communication of cooperating intelligent robots by fuzzy signatures

T. D. Gedeon Á Ballagi L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2009-12-10

Volume: Unknown

Issue: Unknown

Page Range: 1073-1078

Description:

This paper presents two examples of usage of fuzzy signatures in the field of mobile robotics. The first shows a complex lateral drift control method base on fuzzy signatures. This method inspects the motion system of the robot as a whole, unlike as simple parts of a complex system. The state space is written down by fuzzy signatures which add up flexibility, adaptability and learning ability to the system. In the second experiment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems. ©2009 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2009.5277207

Robot cooperation without explicit communication by fuzzy signatures and decision trees

T. D. Gedeon Á Ballagi L. T. Koczy

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1468-1473

Description:

This paper presents a novel action selection method for multi robot task sharing problem. Two autonomous mobile robots try to cooperate for push a box to a goal position. Both robots equipped with object and goal sensing, but do not have explicit communication ability. We explore the use of fuzzy signatures and decision making system to intention guessing and efficient action selection. Virtual reality simulation is used to build and test our proposed algorithm.

Open Access: Yes

DOI: DOI not available

Fuzzy communication and motion control by fuzzy signatures in intelligent mobile robots

T. D. Gedeon Á Ballagi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2009-10-26

Volume: 241

Issue: Unknown

Page Range: 147-164

Description:

This paper presents two examples for the deployment of fuzzy signatures in the field of intelligent mobile robots. The first shows a complex lateral drift control method base on fuzzy signatures. This method considers the motion system of the robot as a whole, unlike as simple parts of a complex system. The state space is written down by fuzzy signatures which add up flexibility, adaptability and learning ability to the system. In the second experiment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems. © 2009 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-03633-0_9

Fuzzy signature and cognitive modelling for complex decision model

T. D. Gedeon L. T. Koczy Kok Wai Wong

Publication Name: Advances in Soft Computing

Publication Date: 2007-12-01

Volume: 42

Issue: Unknown

Page Range: 380-389

Description:

As data is getting more complex and complicated, it is increasingly difficult to construct an effective complex decision model. Two very obvious examples where such a need emerges are in the economic and the medical fields. This paper presents the fuzzy signature and cognitive modeling approach which could improve such decision models. Fuzzy signatures are introduced to handle complex structured data and problems with interdependent features. A fuzzy signature can also be used in cases where data is missing. The proposed fuzzy signature structure will be used in problems that fall into this category. This paper also investigates a novel cognitive model to extend the usage of fuzzy signatures. This Fuzzy Cognitive Signature Modelling will enhance the usability of fuzzy theory in modelling complex systems as well as facilitating complex decision making process based on ill structured information or data. © 2007 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-540-72434-6_38

Fuzzy models and interpolation

J. Botzheim T. D. Gedeon L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2007-10-08

Volume: 217

Issue: Unknown

Page Range: 111-131

Description:

This paper focuses on two essential topics of the fuzzy area. The first is the reduction of fuzzy rule bases. The classical inference methods of fuzzy systems deal with dense rule bases where the universe of discourse is fully covered. By applying sparse or hierarchical rule bases the computational complexity can be decreased. The second subject of the paper is the introduction of some fuzzy rule base identification techniques. In some cases the fuzzy rule base might be given by a human expert, but usually there are only numerical patterns available and an automatic method has to be applied to determine the fuzzy rules. © 2007 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-540-73182-5_6

Context dependent reconstructive communication

T. D. Gedeon L. T. Koczy

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-09-25

Volume: Unknown

Issue: Unknown

Page Range: 13-19

Description:

No description provided

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367354

Learning generalized weighted relevance aggregation operators using levenberg-marquardt method

B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: Proceedings Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro Computing and Evolving Intelligence His Ncei 2006

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

We previously introduced the generalized Weighted Relevance Aggregation Operators (WRAO) for hierarchical fuzzy signatures. WRAO enhances the ability of the fuzzy signature model to adapt to different applications and simplifies the learning of fuzzy signature models from data. In this paper we overcome the practical issues which occur when learning WRAO from data. This paper discuss an algorithm for learning WRAO using the Levenberg-Marquardt (LM) method, which is one of the most sophisticated and widely used gradient based optimization method. Also, this paper shows the successful results of applying the proposed algorithm to extract WRAO for two real world problems namely High Salary Selection and SARS Patient Classification. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/HIS.2006.264917

Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems

J. Botzheim T. D. Gedeon Erich Peter Klement Edwin Lughofer L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 2263-2269

Description:

In this paper a new algorithm for the learning of Takagi-Sugeno fuzzy systems is introduced. In the algorithm different learning techniques are applied for the antecedent and the consequent parameters of the fuzzy system. We propose a hybrid method for the antecedent parameters learning based on the combination of the Bacterial Evolutionary Algorithm (BEA) and the Levenberg-Marquardt (LM) method. For the linear parameters in fuzzy systems appearing in the rule consequents the Least Squares (LS) and the Recursive Least Squares (RLS) techniques are applied, which will lead to a global optimal solution of linear parameter vectors in the least squares sense. Therefore a better performance can be guaranteed than with a complete learning by BEA and LM. The paper is concluded by evaluation results based on high-dimensional test data. These evaluation results compare the new method with some conventional fuzzy training methods with respect to approximation accuracy and model complexity. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2006.1682014

Efficient fuzzy cognitive modeling for unstructured information

T. D. Gedeon L. T. Koczy Kok Wai Wong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 358-363

Description:

This paper presents an efficient fuzzy cognitive modeling which can handle granulation, organisation and causation. This cognitive modeling technique consists of multiple levels where the lowest level includes details required to make a decision or to transfer to the next stage. This Fuzzy Cognitive Modeling will enhance the usability of fuzzy theory in modeling complex systems as well as facilitating complex decision making process based on ill structured or missing information or data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2006.1681737

Generalised weighted relevance aggregation operators for hierarchical fuzzy signatures

J. Botzheim B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: Cimca 2006 International Conference on Computational Intelligence for Modelling Control and Automation Jointly with Iawtic 2006 International Conference on Intelligent Agents Web Technologies

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical Fuzzy Signature Structures. In this paper, we further generalise the weights and the aggregation into a new operator called Weighted Relevance Aggregation Operator (WRAO). WRAO enhances the adaptability of the fuzzy signature model to different applications and simplifies the learning of fuzzy signature models from data. We also show the methodology of learning these aggregation operators from data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/CIMCA.2006.110

On the issue of learning weights from observations for fuzzy signatures

B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: 2006 World Automation Congress Wac 06

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

We investigate the issue of obtaining weights, which are associated with aggregation in fuzzy signatures, from real world data, Our approach will provide a way to extract the relevance of lower levels to the higher levels of the hierarchical fuzzy signature structure. We also handle the non-differentiability of max-min aggregation functions for gradient based learning. A mathematically proved method, which is found in the literature to approximate the derivatives of max-min functions, has been used. Copyright - World Automation Congress (WAC) 2006.

Open Access: Yes

DOI: 10.1109/WAC.2006.376058

Bacterial memetic algorithm for fuzzy rule base optimization

C. Cabrita J. Botzheim T. D. Gedeon Carlos Fonseca A. E. Ruano L. T. Koczy

Publication Name: 2006 World Automation Congress Wac 06

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The LevenbergMarquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques - the bacterial memetic algorithm - was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule extraction. The new method can optimize not only the rules, but can also find the optimal size of the rule base. Copyright - World Automation Congress (WAC) 2006.

Open Access: Yes

DOI: 10.1109/WAC.2006.376057

Fuzzy rule interpolation for multidimensional input spaces with applications: A case study

T. D. Gedeon Domonkos Tikk L. T. Koczy Kok Wai Wong

Publication Name: IEEE Transactions on Fuzzy Systems

Publication Date: 2005-12-01

Volume: 13

Issue: 6

Page Range: 809-819

Description:

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, this may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have been established to solve the problems encountered in processing sparse fuzzy rule bases. In most engineering applications, the use of more than one input variable is common, however, the majority of the fuzzy rule interpolation techniques only present detailed analysis to one input variable case. This paper investigates characteristics of two selected fuzzy rule interpolation techniques for multidimensional input spaces and proposes an improved fuzzy rule interpolation technique to handle multidimensional input spaces. The three methods are compared by means of application examples in the field of petroleum engineering and mineral processing. The results show that the proposed fuzzy rule interpolation technique for multidimensional input spaces can be used in engineering applications. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/TFUZZ.2005.859316

Fuzzy pseudo-thesaurus based clustering of a folkloristic corpus

T. D. Gedeon L. T. Koczy S. Szaszkó

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2005-09-01

Volume: Unknown

Issue: Unknown

Page Range: 126-131

Description:

Automatic thesaurus extraction is essential for modern information retrieval. We develop a method for fuzzy pseudo-thesaurus based on word pair co-occurrence in documents. In this study it is presented, that considering the Word Frequency Degree counted on the whole corpus makes the obtained pseudo-thesaurus usable. Such parameters were found with which most of the obtained pairs of words were validated to be related by human expert. Among the extracted pairs and groups of words the relationship is often looser than synonymy, but they identify the frequently repeated topics of the corpus. We suggest the use of groups of closely related words for the definition of different topics and based on this clustering of the documents were performed.1 © 2005 IEEE.

Open Access: Yes

DOI: DOI not available

Construction of fuzzy signature from data: An example of S ARS pre-clinical diagnosis system

T. D. Gedeon L. T. Koczy Kok Wai Wong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 1649-1654

Description:

There are many areas where objects with very complex and sometimes interdependent features are to be classified; similarities and dissimilarities are to be evaluated. This makes a complex decision model difficult to construct effectively. Fuzzy signatures are introduced to handle complex structured data and interdependent feature problems. Fuzzy signatures can also used in cases where data is missing. This paper presents the concept of a fuzzy signature and how its flexibility can be used to quickly construct a medical pre-clinical diagnosis system. A Severe Acute Respiratory Syndrome (SARS) pre-clinical diagnosis system using fuzzy signatures is constructed as an example to show many advantages of the fuzzy signature. With the use of this fuzzy signature structure, complex decision models in the medical field should be able to be constructed more effectively.

Open Access: Yes

DOI: 10.1109/FUZZY.2004.1375428

Sparse fuzzy systems generation and fuzzy rule interpolation: A practical approach

Sz Kovacs T. D. Gedeon L. T. Koczy None Chong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2003-07-11

Volume: 1

Issue: Unknown

Page Range: 494-499

Description:

In this paper, we explore the use of a sparse fuzzy system generation technique in conjunction with simple projection-based fuzzy rule interpolation, to generate sparse fuzzy systems with relatively few rules whilst still achieving reasonable system accuracy. Through setting a parameter value, the user is able to control, to some extent, the number of rules generated by the rule extraction technique. The rule interpolation approach enables the sparse fuzzy system to maintain a reasonable accuracy. The effectiveness of this approach is validated experimentally.

Open Access: Yes

DOI: DOI not available