Tag: Soft Computing – A Fusion of Foundations, Methodologies and Applications

A dynamic game of coalition formation under ambiguity

Abstract  In a previous paper, we generalized to the mixed strategy case the γ model of coalition formation (introduced by Hart and
Kurz in Econometrica 51(4):1047–1064, 1983) for situations in which players have ambiguous expectations ab…

Abstract  

In a previous paper, we generalized to the mixed strategy case the γ model of coalition formation (introduced by Hart and
Kurz in Econometrica 51(4):1047–1064, 1983) for situations in which players have ambiguous expectations about the formation of the coalitions in which they are not
involved; then we analyzed the corresponding evolutionary games. In this paper, we embody into the model rationality of the
players; it follows that allowing for mixed strategies makes it impossible to construct unequivocally a von Neumann–Morgestein
expected utility function coherent (in the sense of de Finetti B in Sul Significato Soggettivo della Probabilità, Fundamenta Mathematicae, T, vol XVIII, pp
298–329, 1931) to every strategy profile. We find out that if the multiplicity of coherent beliefs problem is approached by considering
“ambiguity loving” players then existence results for classical static equilibria can be obtained in this model. Moreover,
we provide conditions for the game to be dynamically playable and we find how the coalition structure beliefs might evolve
coherently (according) to the evolution of the strategies.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0573-3
  • Authors
    • Giuseppe De Marco, Università di Napoli Parthenope Dipartimento di Statistica e Matematica per la Ricerca Economica Via Medina 40 80133 Naples Italy
    • Maria Romaniello, Seconda Università di Napoli Dipartimento di Strategie Aziendali e Metodologie Quantitative Corso Gran Priorato di Malta 81043 Capua Italy

Automatic summarisation and annotation of microarray data

Abstract  The study of biological processes within cells is based on the measurement of the activity of different molecules, in particular
genes and proteins whose activities are strictly related. The activity of genes is measured through a …

Abstract  

The study of biological processes within cells is based on the measurement of the activity of different molecules, in particular
genes and proteins whose activities are strictly related. The activity of genes is measured through a systematic investigation
carried out by microarrays. Such technology enables the investigation of all the genes of an organism in a single experiment,
encoding meaningful biological information. Nevertheless, the preprocessing of raw microarray data needs automatic tools that
standardise such phase in order to: (a) avoiding errors in analysis phases, and (b) making comparable the results of different
laboratories. The preprocessing problem is as much relevant as considering results obtained from analysis platforms of different
vendors. Nevertheless, there is currently a lack of tools that allow to manage and preprocess multivendor dataset. This paper
presents a software platform (called GSAT, General-purpose Summarisation and Annotation Tool) able to manage and preprocess
microarray data. The GSAT allows the summarisation, normalisation and annotation of multivendor microarray data, using web
services technology. First experiments and results on Affymetrix data samples are also discussed. GSAT is available online
at http://bioingegneria.unicz.it/m-cs as a standalone application or as a plugin of the TMEV microarray data analysis platform.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0600-4
  • Authors
    • Pietro H. Guzzi, University Magna Graecia Bioinformatics Laboratory, Department of Experimental Medicine and Clinic 88100 Catanzaro Italy
    • Maria Teresa Di Martino, T. Campanella Cancer Center, University Magna Graecia Medical Oncology Unit 88100 Catanzaro Italy
    • Giuseppe Tradigo, University Magna Graecia Bioinformatics Laboratory, Department of Experimental Medicine and Clinic 88100 Catanzaro Italy
    • Pierangelo Veltri, University Magna Graecia Bioinformatics Laboratory, Department of Experimental Medicine and Clinic 88100 Catanzaro Italy
    • Pierfrancesco Tassone, T. Campanella Cancer Center, University Magna Graecia Medical Oncology Unit 88100 Catanzaro Italy
    • Pierosandro Tagliaferri, T. Campanella Cancer Center, University Magna Graecia Medical Oncology Unit 88100 Catanzaro Italy
    • Mario Cannataro, University Magna Graecia Bioinformatics Laboratory, Department of Experimental Medicine and Clinic 88100 Catanzaro Italy

Automata theory based on lattice-ordered semirings

Abstract  In this paper, definitions of

K
automata,

K
regular languages,

K
regular expressions and

K
regular grammars based on lattice-ordered semirings are given. It is shown that

K
NFA is equivalent to

K
DFA under some finit…

Abstract  

In this paper, definitions of

K

automata,

K

regular languages,

K

regular expressions and

K

regular grammars based on lattice-ordered semirings are given. It is shown that

K

NFA is equivalent to

K

DFA under some finite condition, the Pump Lemma holds if

K

is finite, and

Ke

NFA is equivalent to

K

NFA. Further, it is verified that the concatenation of

K

regular languages remains a

K

regular language. Similar to classical cases and automata theory based on lattice-ordered monoids, it is also found that

K

NFA,

K

regular expressions and

K

regular grammars are equivalent to each other when

K

is a complete lattice.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0565-3
  • Authors
    • Xian Lu, AMSS Institute of Mathematics, Academia Sinica Beijing 100190 People’s Republic of China
    • Yun Shang, AMSS Institute of Mathematics, Academia Sinica Beijing 100190 People’s Republic of China
    • Ruqian Lu, AMSS Institute of Mathematics, Academia Sinica Beijing 100190 People’s Republic of China

Comparing early and late data fusion methods for gene expression prediction

Abstract  The most basic molecular mechanism enabling a living cell to dynamically adapt to variation occurring in its intra and extracellular
environment is constituted by its ability to regulate the expression of many of its genes. At biom…

Abstract  

The most basic molecular mechanism enabling a living cell to dynamically adapt to variation occurring in its intra and extracellular
environment is constituted by its ability to regulate the expression of many of its genes. At biomolecular level, this ability
is mainly due to interactions occurring between regulatory motifs located in the core promoter regions and the transcription
factors. A crucial question investigated by recently published works is if, and at what extent, the transcription patterns
of large sets of genes can be predicted using only information encoded in the promoter regions. Even if encouraging results
were obtained in gene expression patterns prediction experiments the assumption that all the signals required for the regulation
of gene expression are contained in the gene promoter regions is an oversimplification as pointed out by recent findings demonstrating
the existence of many regulatory levels involved in the fine modulation of gene transcription levels. In this contribution,
we investigate the potential improvement in gene expression prediction performances achievable by using early and late data
integration methods in order to provide a complete overview of the capabilities of data fusion approaches in a problem that
can be annoverated among the most difficult in modern bioinformatics.

  • Content Type Journal Article
  • Pages 1-8
  • DOI 10.1007/s00500-010-0599-6
  • Authors
    • Matteo Re, Universitá degli studi di Milano Dipartimento di Scienze dell’Informazione, DSI via Comelico 39 Milan Italy

Advances in Computational Intelligence and Bioinformatics

Advances in Computational Intelligence and Bioinformatics
Content Type Journal ArticlePages 1-2DOI 10.1007/s00500-010-0595-xAuthors
Francesco Masulli, Università di Genova DISI, Dipartimento di Informatica e Scienze, dell’Informazione Via Dodecan…

Advances in Computational Intelligence and Bioinformatics

  • Content Type Journal Article
  • Pages 1-2
  • DOI 10.1007/s00500-010-0595-x
  • Authors
    • Francesco Masulli, Università di Genova DISI, Dipartimento di Informatica e Scienze, dell’Informazione Via Dodecaneso 35 Genoa Italy
    • Roberto Tagliaferri, Università di Salerno NeuRoNe Lab, DMI, Dipartimento di Matematica e Informatica Via Ponte don Melillo Fisciano (SA) Italy

Rule acquisition and attribute reduction in real decision formal contexts

Abstract  Formal Concept Analysis of real set formal contexts is a generalization of classical formal contexts. By dividing the attributes
into condition attributes and decision attributes, the notion of real decision formal contexts is intr…

Abstract  

Formal Concept Analysis of real set formal contexts is a generalization of classical formal contexts. By dividing the attributes
into condition attributes and decision attributes, the notion of real decision formal contexts is introduced. Based on an
implication mapping, problems of rule acquisition and attribute reduction of real decision formal contexts are examined. The
extraction of “if–then” rules from the real decision formal contexts, and the approach to attribute reduction of the real
decision formal contexts are discussed. By the proposed approach, attributes which are non-essential to the maximal s rules or l rules (to be defined later in the text) can be removed. Furthermore, discernibility matrices and discernibility functions
for computing the attribute reducts of the real decision formal contexts are constructed to determine all attribute reducts
of the real set formal contexts without affecting the results of the acquired maximal s rules or l rules.

  • Content Type Journal Article
  • Pages 1-14
  • DOI 10.1007/s00500-010-0578-y
  • Authors
    • Hong-Zhi Yang, Xi’an Jiaotong University Faculty of Science Xi’an 710049 Shaan’xi People’s Republic of China
    • Leung Yee, University of Hong Kong Department of Geography and Resource Management, Center for Environmental Policy and Resource Management Hong Kong People’s Republic of China
    • Ming-Wen Shao, Shihezi University College of Information Science and Technology Shihezi 832000 Xinjiang People’s Republic of China

History mechanism supported differential evolution for chess evaluation function tuning

Abstract  This paper presents a differential evolution (DE) based approach to chess evaluation function tuning. DE with opposition-based
optimization is employed and upgraded with a history mechanism to improve the evaluation of individuals …

Abstract  

This paper presents a differential evolution (DE) based approach to chess evaluation function tuning. DE with opposition-based
optimization is employed and upgraded with a history mechanism to improve the evaluation of individuals and the tuning process.
The general idea is based on individual evaluations according to played games through several generations and different environments.
We introduce a new history mechanism which uses an auxiliary population containing good individuals. This new mechanism ensures
that good individuals remain within the evolutionary process, even though they died several generations back and later can
be brought back into the evolutionary process. In such a manner the evaluation of individuals is improved and consequently
the whole tuning process.

  • Content Type Journal Article
  • Pages 1-17
  • DOI 10.1007/s00500-010-0593-z
  • Authors
    • B. Bošković, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000 Maribor, Slovenia
    • J. Brest, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000 Maribor, Slovenia
    • A. Zamuda, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000 Maribor, Slovenia
    • S. Greiner, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000 Maribor, Slovenia
    • V. Žumer, Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000 Maribor, Slovenia

Covariance matrix self-adaptation evolution strategies and other metaheuristic techniques for neural adaptive learning

Abstract  A covariance matrix self-adaptation evolution strategy (CMSA-ES) was compared with several metaheuristic techniques for multilayer
perceptron (MLP)-based function approximation and classification. Function approximation was based o…

Abstract  

A covariance matrix self-adaptation evolution strategy (CMSA-ES) was compared with several metaheuristic techniques for multilayer
perceptron (MLP)-based function approximation and classification. Function approximation was based on simulations of several
2D functions and classification analysis was based on nine cancer DNA microarray data sets. Connection weight learning by
MLPs was carried out using genetic algorithms (GA–MLP), covariance matrix self-adaptation-evolution strategies (CMSA-ES–MLP),
back-propagation gradient-based learning (MLP), particle swarm optimization (PSO–MLP), and ant colony optimization (ACO–MLP).
During function approximation runs, input-side activation functions evaluated included linear, logistic, tanh, Hermite, Laguerre,
exponential, and radial basis functions, while the output-side function was always linear. For classification, the input-side
activation function was always logistic, while the output-side function was always regularized softmax. Self-organizing maps
and unsupervised neural gas were used to reduce dimensions of original gene expression input features used in classification.
Results indicate that for function approximation, use of Hermite polynomials for activation functions at hidden nodes with
CMSA-ES–MLP connection weight learning resulted in the greatest fitness levels. On average, the most elite chromosomes were
observed for MLP (

MSE=0.4977

), CMSA-ES–MLP (0.6484), PSO–MLP (0.7472), ACO–MLP (1.3471), and GA–MLP (1.4845). For classification analysis, overall average
performance of classifiers used was 92.64% (CMSA-ES–MLP), 92.22% (PSO–MLP), 91.30% (ACO–MLP), 89.36% (MLP), and 60.72% (GA–MLP).
We have shown that a reliable approach to function approximation can be achieved through application of MLP connection weight
learning when the assumed function is unknown. In this scenario, the MLP architecture itself defines the equation used for
solving the unknown parameters relating input and output target values. A major drawback of implementing CMSA-ES into an MLP
is that when the number of MLP weights is large, the

O(N3)

Cholesky factorization becomes a bottleneck for performance. As an alternative, feature reduction using SOM and NG can greatly
enhance performance of CMSA-ES–MLP by reducing

N.

Future research into the speeding up of Cholesky factorization for CMSA-ES will be helpful in overcoming time complexity
problems related to a large number of connection weights.

  • Content Type Journal Article
  • Pages 1-13
  • DOI 10.1007/s00500-010-0598-7
  • Authors
    • Leif E. Peterson, Center for Biostatistics, The Methodist Hospital Research Institute, Houston, TX 77030, USA

Hedges and successors in basic algebras

Abstract  The concept of hedge was introduced by Zadeh in the sake to amplify true values of linguistic terms. It was used by Bělohlávek
and Vychodil for formal concept analysis of unsharp reasoning. The concept of successor was introduced…

Abstract  

The concept of hedge was introduced by Zadeh in the sake to amplify true values of linguistic terms. It was used by Bělohlávek
and Vychodil for formal concept analysis of unsharp reasoning. The concept of successor was introduced by Caicedo and Cignoli
for study of intuitionistic connectives and used by San Martín, Castiglioni, Menni and Sagastume in Heyting algebras. Since
basic algebras form an algebraic tool for simultaneous treaty of many-valued logics and logics of quantum mechanics, it arises
a natural question of generalization of these concepts also for basic algebras. This motivated our investigations on hedges
and successors.

  • Content Type Journal Article
  • Pages 1-6
  • DOI 10.1007/s00500-010-0570-6
  • Authors
    • Ivan Chajda, Palacký University Olomouc Department of Algebra and Geometry, Faculty of Sciences třída 17. listopadu 12 771 46 Olomouc Czech Republic

On intuitionistic fuzzy topologies based on intuitionistic fuzzy reflexive and transitive relations

Abstract  Topologies and rough set theory are widely used in the research field of machine learning and cybernetics. An intuitionistic
fuzzy rough set, which is the result of approximation of an intuitionistic fuzzy set with respect to an in…

Abstract  

Topologies and rough set theory are widely used in the research field of machine learning and cybernetics. An intuitionistic
fuzzy rough set, which is the result of approximation of an intuitionistic fuzzy set with respect to an intuitionistic fuzzy
approximation space, is an extension of fuzzy rough sets. For further studying the theories and applications of intuitionistic
fuzzy rough sets, in this paper, we investigate the topological structures of intuitionistic fuzzy rough sets. We show that
an intuitionistic fuzzy rough approximation space can induce an intuitionistic fuzzy topological space in the sense of Lowen
if and only if the intuitionistic fuzzy relation in the approximation space is reflexive and transitive. We also examine the
sufficient and necessary conditions that an intuitionistic fuzzy topological space can be associated with an intuitionistic
fuzzy reflexive and transitive relation such that the induced lower and upper intuitionistic fuzzy rough approximation operators
are, respectively, the intuitionistic fuzzy interior and closure operators of the given topology.

  • Content Type Journal Article
  • Pages 1-12
  • DOI 10.1007/s00500-010-0576-0
  • Authors
    • Wei-Zhi Wu, Zhejiang Ocean University School of Mathematics, Physics and Information Science Zhoushan 316004 Zhejiang People’s Republic of China
    • Lei Zhou, Chengdu University of Information Technology College of Mathematics Chengdu 610225 Sichuan People’s Republic of China