Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949470
C. J. A. B. Filho, Marcos A. C. Oliveira, D. R. C. Silva, R. A. Santana
Although some interesting routing algorithms based on HNN were already proposed, they are slower when compared to other routing algorithms. Since HNN are inherently parallel, they are suitable for parallel implementations, such as Graphic Processing Units (GPU). In this paper we propose a fast routing algorithm based on Hopfield Neural Networks (HNN) for GPU, considering some implementation issues. We analyzed the memory bottlenecks, the complexity of the HNN and how the kernel functions should be implemented. We performed simulations for five different variations of the routing algorithm for two communication network topologies. We achieved speed-ups up to 55 when compared to the simplest version implemented in GPU and up to 40 when compared to the CPU version. These new results suggest that it is possible to use the HNN for routing in real networks.
{"title":"Optimizing a routing algorithm based on Hopfield Neural Networks for Graphic Processing Units","authors":"C. J. A. B. Filho, Marcos A. C. Oliveira, D. R. C. Silva, R. A. Santana","doi":"10.1109/FOCI.2011.5949470","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949470","url":null,"abstract":"Although some interesting routing algorithms based on HNN were already proposed, they are slower when compared to other routing algorithms. Since HNN are inherently parallel, they are suitable for parallel implementations, such as Graphic Processing Units (GPU). In this paper we propose a fast routing algorithm based on Hopfield Neural Networks (HNN) for GPU, considering some implementation issues. We analyzed the memory bottlenecks, the complexity of the HNN and how the kernel functions should be implemented. We performed simulations for five different variations of the routing algorithm for two communication network topologies. We achieved speed-ups up to 55 when compared to the simplest version implemented in GPU and up to 40 when compared to the CPU version. These new results suggest that it is possible to use the HNN for routing in real networks.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133727917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949472
P. Cordero, M. Enciso, Á. Mora, I. Guzmán, J. M. Rodríguez-Jiménez
In this work, an extension of the database relational model which incorporates vague or imprecise data is presented. Specifically, we extend the concept of functional dependency to Fuzzy Attributes Tables. This extension is based on the use of a residuated lattice as a truthfulness value set. For this goal, the domains are enriched with fuzzy similarity relations, the atomic values of the tables become fuzzy, and the functional dependencies are also fuzzy and based on the similarity relations. Moreover, we introduce a sound and complete axiomatic system to manipulate these dependencies, named Simplification Logic for fuzzy functional dependencies.
{"title":"Specification and inference of fuzzy attributes","authors":"P. Cordero, M. Enciso, Á. Mora, I. Guzmán, J. M. Rodríguez-Jiménez","doi":"10.1109/FOCI.2011.5949472","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949472","url":null,"abstract":"In this work, an extension of the database relational model which incorporates vague or imprecise data is presented. Specifically, we extend the concept of functional dependency to Fuzzy Attributes Tables. This extension is based on the use of a residuated lattice as a truthfulness value set. For this goal, the domains are enriched with fuzzy similarity relations, the atomic values of the tables become fuzzy, and the functional dependencies are also fuzzy and based on the similarity relations. Moreover, we introduce a sound and complete axiomatic system to manipulate these dependencies, named Simplification Logic for fuzzy functional dependencies.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128857646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949480
J. Kacprzyk, S. Zadrożny
The concept of a bipolar query, meant as a database query that involves both positive and negative conditions is discussed from the point of view of flexible database querying. A new possible perspective is outlined which is related to the modeling of affects that play a crucial role in real world human centric decision making, and are also known to involve a positive and negative valuation which are the crucial elements of bipolar queries. The aggregation of the matching degrees against the negative and positive conditions to derive an overall matching degree is considered taking into account the Lacroix and Lavency approach [1] for bipolar queries as the point of departure. It is shown that the use of a multiple valued logic based formalism for the representation of positive and negative evaluations boils down to a logical type evaluation function that is in line with Grabisch, Greco and Pirlot's [2] general approach to bivariate bipolar multicriteria decision making. Then, an affective computing perspective - in its affect and judgment related setting that is decision making oriented - is outlined and advocated.
{"title":"Affect, judgment and decision making: Some inspirations for bipolar querying","authors":"J. Kacprzyk, S. Zadrożny","doi":"10.1109/FOCI.2011.5949480","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949480","url":null,"abstract":"The concept of a bipolar query, meant as a database query that involves both positive and negative conditions is discussed from the point of view of flexible database querying. A new possible perspective is outlined which is related to the modeling of affects that play a crucial role in real world human centric decision making, and are also known to involve a positive and negative valuation which are the crucial elements of bipolar queries. The aggregation of the matching degrees against the negative and positive conditions to derive an overall matching degree is considered taking into account the Lacroix and Lavency approach [1] for bipolar queries as the point of departure. It is shown that the use of a multiple valued logic based formalism for the representation of positive and negative evaluations boils down to a logical type evaluation function that is in line with Grabisch, Greco and Pirlot's [2] general approach to bivariate bipolar multicriteria decision making. Then, an affective computing perspective - in its affect and judgment related setting that is decision making oriented - is outlined and advocated.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122331612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949467
P. J. Morcillo, G. Moreno
Fuzzy extensions of logic programming often require the notion of reductant to ensure completeness when working with some lattices modeling the concept of truth degree beyond the simpler case of true and false. Initially introduced in the context of generalized annotated logic programming, some adaptations of this theoretical tool have been proposed for the more recent and flexible framework of multi-adjoint logic programming. To the best of our knowledge, all of them suffer the important problem of usually requiring an infinite set of reductants (one for each ground atom) for being added to a given program in order to guarantee its completeness. The main goal of this paper is the introduction of a generalized notion of reductant, called G-reductant, which only depends on (a finite number of) predicate symbols instead of ground atoms (whose number is always infinite for programs considering at least a non constant function symbol in their signature). More exactly, given a predicate p/n in the signature of a fuzzy program p, we generate just a single G-reductant with head p(X1, … , Xn) (being X1, … , Xn different variable symbols) which covers all the possible calls to p in a completely safe way. Since the number of G-reductants is finite for programs with a finite number of predicates, our notion can be really applied in practice in contrast with older versions of reductants which are only applicable at a non-practical, but purely theoretical level.
{"title":"Improving completeness in multi-adjoint logic computations via general reductants","authors":"P. J. Morcillo, G. Moreno","doi":"10.1109/FOCI.2011.5949467","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949467","url":null,"abstract":"Fuzzy extensions of logic programming often require the notion of reductant to ensure completeness when working with some lattices modeling the concept of truth degree beyond the simpler case of true and false. Initially introduced in the context of generalized annotated logic programming, some adaptations of this theoretical tool have been proposed for the more recent and flexible framework of multi-adjoint logic programming. To the best of our knowledge, all of them suffer the important problem of usually requiring an infinite set of reductants (one for each ground atom) for being added to a given program in order to guarantee its completeness. The main goal of this paper is the introduction of a generalized notion of reductant, called G-reductant, which only depends on (a finite number of) predicate symbols instead of ground atoms (whose number is always infinite for programs considering at least a non constant function symbol in their signature). More exactly, given a predicate p/n in the signature of a fuzzy program p, we generate just a single G-reductant with head p(X1, … , Xn) (being X1, … , Xn different variable symbols) which covers all the possible calls to p in a completely safe way. Since the number of G-reductants is finite for programs with a finite number of predicates, our notion can be really applied in practice in contrast with older versions of reductants which are only applicable at a non-practical, but purely theoretical level.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131175117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949461
L. Mak, G. Ng, Godfrey Lim, K. Mao
Real-world datasets usually involve class overlap. It has been observed that, in general, the performance of clustering algorithms degrade with the increasing overlapping degree. The main challenge for clustering overlapping data is the determination of the appropriate number of clusters and division of the overlapping region. This paper proposes a novel method based on Fuzzy ART clustering to handle the overlapping data without demanding a priori the number of clusters. With the use of over-clustering and merging mechanism, Merging Fuzzy ART (MFuART) generates the number of clusters automatically and with good cluster quality.
{"title":"A merging Fuzzy ART clustering algorithm for overlapping data","authors":"L. Mak, G. Ng, Godfrey Lim, K. Mao","doi":"10.1109/FOCI.2011.5949461","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949461","url":null,"abstract":"Real-world datasets usually involve class overlap. It has been observed that, in general, the performance of clustering algorithms degrade with the increasing overlapping degree. The main challenge for clustering overlapping data is the determination of the appropriate number of clusters and division of the overlapping region. This paper proposes a novel method based on Fuzzy ART clustering to handle the overlapping data without demanding a priori the number of clusters. With the use of over-clustering and merging mechanism, Merging Fuzzy ART (MFuART) generates the number of clusters automatically and with good cluster quality.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127335427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949464
J. A. Brown
The well known game Iterated Prisoner's Dilemma (IPD) is examined as a test case for a new algorithm of genetic search known as Multiple Agent Genetic Networks (MAGnet). MAGnet facilitates the movement of not just the agents, but also the problem instances which a population of agents is working to solve in parallel. This allows for simultaneous classification of problem instances and search for solution to those problems. As this is an initial study, there is a focus on the ability of MAGnet to classify problem instances of IPD playing agents. A problem instance of IPD is a single opponent. A good classification method, called fingerprinting, for IPD exists and allows for verification of the comparison. Results found by MAGnet are shown to be logical classifications of the problems based upon player strategy. A subpopulation collapse effect is shown which allows the location of both difficult problem instances and the existence of general solutions to a problem.
{"title":"Multiple Agent Genetic Networks for Iterated Prisoner's Dilemma","authors":"J. A. Brown","doi":"10.1109/FOCI.2011.5949464","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949464","url":null,"abstract":"The well known game Iterated Prisoner's Dilemma (IPD) is examined as a test case for a new algorithm of genetic search known as Multiple Agent Genetic Networks (MAGnet). MAGnet facilitates the movement of not just the agents, but also the problem instances which a population of agents is working to solve in parallel. This allows for simultaneous classification of problem instances and search for solution to those problems. As this is an initial study, there is a focus on the ability of MAGnet to classify problem instances of IPD playing agents. A problem instance of IPD is a single opponent. A good classification method, called fingerprinting, for IPD exists and allows for verification of the comparison. Results found by MAGnet are shown to be logical classifications of the problems based upon player strategy. A subpopulation collapse effect is shown which allows the location of both difficult problem instances and the existence of general solutions to a problem.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134398092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949478
J. Merigó
We develop a new method for decision making based on the use of probabilities, weighted averages and ordered weighted averaging (OWA) operators. We analyze a method that it is able to deal with several aggregation structures thus obtaining a more general formulation that represents the information in a more complete way. We introduce a new aggregation operator that aggregates a wide range of other aggregation operators. Therefore, we can include in the same formulation a wide range of concepts and representing how relevant they are in the aggregation. We call it the unified aggregation operator. By using this aggregation operator we can deal with a wide range of complex structures, for example, we can aggregate in a decision making problem several structures of probabilities, weighted averages and OWA operators. Thus, the information we provide is more complete because in real world problems the information comes from different sources and this needs to be considered in the aggregation process. We study the applicability of this new approach and we see that it is very broad because real world problems are better assessed with this new model. We focus on a multi-person decision making example where we use several structures of probabilities, weighted averages and OWA operators, thus representing the subjective and the objective information and the attitudinal character in a more complete way.
{"title":"Decision making with probabilities, weighted averages and OWA operators","authors":"J. Merigó","doi":"10.1109/FOCI.2011.5949478","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949478","url":null,"abstract":"We develop a new method for decision making based on the use of probabilities, weighted averages and ordered weighted averaging (OWA) operators. We analyze a method that it is able to deal with several aggregation structures thus obtaining a more general formulation that represents the information in a more complete way. We introduce a new aggregation operator that aggregates a wide range of other aggregation operators. Therefore, we can include in the same formulation a wide range of concepts and representing how relevant they are in the aggregation. We call it the unified aggregation operator. By using this aggregation operator we can deal with a wide range of complex structures, for example, we can aggregate in a decision making problem several structures of probabilities, weighted averages and OWA operators. Thus, the information we provide is more complete because in real world problems the information comes from different sources and this needs to be considered in the aggregation process. We study the applicability of this new approach and we see that it is very broad because real world problems are better assessed with this new model. We focus on a multi-person decision making example where we use several structures of probabilities, weighted averages and OWA operators, thus representing the subjective and the objective information and the attitudinal character in a more complete way.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116393915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-01DOI: 10.1109/FOCI.2011.5949473
F. Díaz-Hermida, Alberto Bugarín-Diz
In this paper we discuss how semi-fuzzy quantifiers are a useful tool for modeling linguistic summaries from data in two aspects: how they provide a systematic mechanism for performing the data summarization task involving fuzzy quantifiers that are different from the usual unary and binary ones and also how they can be used for the detection of quantified patterns in data.
{"title":"Semi-fuzzy quantifiers as a tool for building linguistic summaries of data patterns","authors":"F. Díaz-Hermida, Alberto Bugarín-Diz","doi":"10.1109/FOCI.2011.5949473","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949473","url":null,"abstract":"In this paper we discuss how semi-fuzzy quantifiers are a useful tool for modeling linguistic summaries from data in two aspects: how they provide a systematic mechanism for performing the data summarization task involving fuzzy quantifiers that are different from the usual unary and binary ones and also how they can be used for the detection of quantified patterns in data.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127422250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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