Category: Uncategorized

The variety generated by semi-Heyting chains

Abstract  The purpose of this paper was to investigate the structure of semi-Heyting chains and the variety

CSH
generated by them. We determine the number of non-isomorphic n-element semi-Heyting chains. As a contribution to the study of t…

Abstract  

The purpose of this paper was to investigate the structure of semi-Heyting chains and the variety

CSH

generated by them. We determine the number of non-isomorphic n-element semi-Heyting chains. As a contribution to the study of the lattice of subvarieties of

CSH,

we investigate the inclusion relation between semi-Heyting chains. Finally, we provide equational bases for

CSH

and for the subvarieties of

CSH

introduced in [5].

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0604-0
  • Authors
    • M. Abad, Universidad Nacional del Sur Departamento de Matemática 8000 Bahía Blanca Argentina
    • J. M. Cornejo, Universidad Nacional del Sur Departamento de Matemática 8000 Bahía Blanca Argentina
    • J. P. Díaz Varela, Universidad Nacional del Sur Departamento de Matemática 8000 Bahía Blanca Argentina

GP (by any name) on RadioLab

Hod Lipson and Michael Schmidt were on the ever-entertaining RadioLab (in the last segment of this show on “Limits”), discussing their remarkable work on “Distilling Free-Form Natural Laws from Experimental Data” that was published in Science last year…

Hod Lipson and Michael Schmidt were on the ever-entertaining RadioLab (in the last segment of this show on “Limits”), discussing their remarkable work on “Distilling Free-Form Natural Laws from Experimental Data” that was published in Science last year. Although I don’t think they call it GP explicitly in the radio show or even in the main Science article, GP is central to their work, as is explained in detail in the article’s Supporting Online Material (links to Science are not free).

A review of the nondeterministic waiting time algorithm

Abstract  We provide the description for the nondeterministic waiting time (NWT) algorithm, a biochemical modeling approach based on
the membrane systems paradigm of computation. The technique provides a unique (different to Gillespie’s al…

Abstract  

We provide the description for the nondeterministic waiting time (NWT) algorithm, a biochemical modeling approach based on
the membrane systems paradigm of computation. The technique provides a unique (different to Gillespie’s algorithm or ODE modeling)
perspective on the biochemical evolution of the cell. That is, depending on the reactions and molecular multiplicities of
a given model, our simulator is capable of producing results comparable to the alternative techniques—continuous and deterministic
or discrete and stochastic. Some results for sample models are given, illustrating the differences between the NWT algorithm,
the Gillespie algorithm, and the solutions to systems of ordinary differential equations. We have previously used this simulation
technique to address issues surrounding Fas-induced apoptosis in cancerous cells and so-called latent HIV-infected cells.

  • Content Type Journal Article
  • Pages 1-11
  • DOI 10.1007/s11047-010-9195-z
  • Authors
    • John Jack, IfM Louisiana Tech University Department of Computer Science P.O. Box 10348 Ruston LA 71272 USA
    • Andrei Păun, IfM Louisiana Tech University Department of Computer Science P.O. Box 10348 Ruston LA 71272 USA
    • Alfonso Rodríguez-Patón, Universidad Politécnica de Madrid Facultad de Informática, Departamento de Inteligencia Artificial Campus de Montegancedo S/N 28660 Boadilla del Monte, Madrid Spain

Heuristic search for optimizing diffusion of influence in a social network under the resource constraint

Abstract  The diffusion of influence in a social network has been recently investigated in various fields. In this paper, we study the
problem of minimizing the expected complete influence time of a social network under the resource constrai…

Abstract  

The diffusion of influence in a social network has been recently investigated in various fields. In this paper, we study the
problem of minimizing the expected complete influence time of a social network under the resource constraint. We focus on
the case where the budget for influencing the initial target set of individuals is limited. The incremental chance model is
adopted to characterize the diffusion of influence, and a lower bound for the expected complete influence time is presented.
In order to solve the problem effectively, we modify the well-known heuristic search approach, the A* algorithm, and provide a series of strategies for designing the heuristic functions. Finally, we perform experiments to
show that the proposed algorithm generally performs better than widely used trivial heuristic methods.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0601-3
  • Authors
    • Yaodong Ni, University of International Business and Economics School of Information Technology and Management Beijing China
    • Zhi-Qiang Liu, City University of Hong Kong School of Creative Media Hong Kong China

Pattern classification based on k locally constrained line

Abstract  A simple yet effective learning algorithm, k locally constrained line (k-LCL), is presented for pattern classification. In k-LCL, any two prototypes of the same class are extended to a constrained line (CL), through which the repres…

Abstract  

A simple yet effective learning algorithm, k locally constrained line (k-LCL), is presented for pattern classification. In k-LCL, any two prototypes of the same class are extended to a constrained line (CL), through which the representational capacity
of the training set is largely improved. Because each CL is adjustable in length, k-LCL can well avoid the “intersecting” of training subspaces in most traditional feature classifiers. Moreover, to speed up
the calculation, k-LCL classifies an unknown sample focusing only on its local CLs in each class. Experimental results, obtained on both synthetic
and real-world benchmark data sets, show that the proposed method has better accuracy and efficiency than most existing feature
line methods.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0602-2
  • Authors
    • Jianjun Qing, Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai China
    • Hong Huo, Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai China
    • Tao Fang, Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai China

A new initialization procedure for the distributed estimation of distribution algorithms

Abstract  Estimation of distribution algorithms (EDAs) are one of the most promising paradigms in today’s evolutionary computation.
In this field, there has been an incipient activity in the so-called parallel estimation of distribution al…

Abstract  

Estimation of distribution algorithms (EDAs) are one of the most promising paradigms in today’s evolutionary computation.
In this field, there has been an incipient activity in the so-called parallel estimation of distribution algorithms (pEDAs).
One of these approaches is the distributed estimation of distribution algorithms (dEDAs). This paper introduces a new initialization
mechanism for each of the populations of the islands based on the Voronoi cells. To analyze the results, a series of different
experiments using the benchmark suite for the special session on Real-parameter Optimization of the IEEE CEC 2005 conference
has been carried out. The results obtained suggest that the Voronoi initialization method considerably improves the performance
obtained from a traditional uniform initialization.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0603-1
  • Authors
    • Santiago Muelas, Universidad Politécnica de Madrid Department of Computer Systems Architecture and Technology, Facultad de Informática Madrid Spain
    • José-María Peña, Universidad Politécnica de Madrid Department of Computer Systems Architecture and Technology, Facultad de Informática Madrid Spain
    • Antonio LaTorre, Universidad Politécnica de Madrid Department of Computer Systems Architecture and Technology, Facultad de Informática Madrid Spain
    • Víctor Robles, Universidad Politécnica de Madrid Department of Computer Systems Architecture and Technology, Facultad de Informática Madrid Spain

A neural network-based multi-agent classifier system with a Bayesian formalism for trust measurement

Abstract  In this paper, a neural network (NN)-based multi-agent classifier system (MACS) utilising the trust-negotiation-communication
(TNC) reasoning model is proposed. A novel trust measurement method, based on the combination of Bayesian…

Abstract  

In this paper, a neural network (NN)-based multi-agent classifier system (MACS) utilising the trust-negotiation-communication
(TNC) reasoning model is proposed. A novel trust measurement method, based on the combination of Bayesian belief functions,
is incorporated into the TNC model. The Fuzzy Min-Max (FMM) NN is used as learning agents in the MACS, and useful modifications
of FMM are proposed so that it can be adopted for trust measurement. Besides, an auctioning procedure, based on the sealed
bid method, is applied for the negotiation phase of the TNC model. Two benchmark data sets are used to evaluate the effectiveness
of the proposed MACS. The results obtained compare favourably with those from a number of machine learning methods. The applicability
of the proposed MACS to two industrial sensor data fusion and classification tasks is also demonstrated, with the implications
analysed and discussed.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0592-0
  • Authors
    • Anas Quteishat, Al-Balqa’ Applied University Department of Computer Engineering, Faculty of Engineering Technology Al-Salt Jordan
    • Chee Peng Lim, University of Science Malaysia School of Electrical and Electronic Engineering Engineering Campus, 14300 Nibong Tebal Penang Malaysia
    • Junita Mohamad Saleh, University of Science Malaysia School of Electrical and Electronic Engineering Engineering Campus, 14300 Nibong Tebal Penang Malaysia
    • Jeffrey Tweedale, University of South Australia School of Electrical and Information Engineering Adelaide Australia
    • Lakhmi C. Jain, University of South Australia School of Electrical and Information Engineering Adelaide Australia

State operators on GMV algebras

Abstract  Flaminio and Montagna recently introduced state

MV
algebras as

MV
algebras with an internal state in the form of a unary operation. Di Nola and Dvurečenskij further presented a stronger variation
of state

MV
algebras call…

Abstract  

Flaminio and Montagna recently introduced state

MV

algebras as

MV

algebras with an internal state in the form of a unary operation. Di Nola and Dvurečenskij further presented a stronger variation
of state

MV

algebras called state-morphism

MV

algebras. In the paper we present state

GMV

algebras and state-morphism

GMV

algebras which are non-commutative generalizations of the mentioned algebras.

  • Content Type Journal Article
  • DOI 10.1007/s00500-010-0568-0
  • Authors
    • Jiří Rachůnek, Palacký University Department of Algebra and Geometry, Faculty of Sciences Tomkova 40 779 00 Olomouc Czech Republic
    • Dana Šalounová, VŠB-Technical University Ostrava Department of Mathematical Methods in Economy, Faculty of Economics Sokolská 33 701 21 Ostrava Czech Republic

Automatic Reproduction of a Genius Algorithm: Strassen’s Algorithm Revisited by Genetic Search

In 1968, Volker Strassen, a young German mathematician, announced a clever algorithm to reduce the asymptotic complexity of nÿn matrix multiplication from the order of n 3 to n 2.81. It soon became one of the most famous scientific discoveries in the …

In 1968, Volker Strassen, a young German mathematician, announced a clever algorithm to reduce the asymptotic complexity of nÿn matrix multiplication from the order of n 3 to n 2.81. It soon became one of the most famous scientific discoveries in the 20th century and provoked numerous studies by other mathematicians to improve upon it. Although a number of improvements have been made, Strassen’s algorithm is still optimal in his original framework, the bilinear systems of 2 ÿ 2 matrix multiplication, and people are still curious how Strassen developed his algorithm. We examined it to see if we could automatically reproduce Strassen’s discovery using a search algorithm and find other algorithms of the same quality. In total, we found 608 algorithms that have the same quality as Strassen’s, including Strassen’s original algorithm. We partitioned the algorithms into nine different groups based on the way they are constructed. This paper was made possible by the combination of genetic search and linear-algebraic techniques. To the best of our knowledge, this is the first work that automatically reproduced Strassen’s algorithm, and furthermore, discovered new algorithms with equivalent asymptotic complexity using a search algorithm.