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2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)

Date 13-15 Dec. 2006

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Displaying Results 1 - 25 of 78
  • Sixth International Conference on Hybrid Intelligent Systems - Cover

    Publication Year: 2006, Page(s): c1
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  • Sixth International Conference on Hybrid Intelligent Systems-Title

    Publication Year: 2006, Page(s): i
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  • Sixth International Conference on Hybrid Intelligent Systems-Copyright

    Publication Year: 2006, Page(s): iv
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  • Sixth International Conference on Hybrid Intelligent Systems - TOC

    Publication Year: 2006, Page(s):v - x
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  • Welcome from the Organizing Chairs

    Publication Year: 2006, Page(s): xi
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  • Conference Committees

    Publication Year: 2006, Page(s): xii
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  • Is That Possible? (Or is it Probable?)

    Publication Year: 2006, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (114 KB) | HTML iconHTML

    In settings where we have significant amounts of data, the probability of events occurring can be calculated. But life is not like that. Human beings must cope with situations where we encounter only a small number of events, handle ambiguous and imprecise information, and respond correctly. Also, arguably, possibility values are more relevant to human beings in the understanding of risk and dange... View full abstract»

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  • Status and Perspective of Intelligent System Design Automation

    Publication Year: 2006, Page(s): 2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (121 KB)

    Intelligent systems have become both ubiquitous and more and more powerful and complex in the last decade. They base on an increasing variety of sensorial input, hybrid algorithms, and integrated, electronic embodiment. In particular, with the rapid advance of wireless and low-power implementation, new application fields, such as sensor networks or ambient intelligence gain momentum. While efficie... View full abstract»

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  • Light-Weight Evolutionary Computation for Complex Image-Processing Applications

    Publication Year: 2006, Page(s): 3
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (132 KB)

    The expedience of today's image-processing applications is not any longer based on the performance of a single algorithm alone. These systems appear to be complex frameworks with a lot of subtasks that are solved by specific algorithms, adaptation procedures, data handling, scheduling, and parameter choices. The venture of using computational intelligence (CI) in such a context, thus, is not a mat... View full abstract»

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  • Monitoring Genetic Variations in Variable Length Evolutionary Algorithms

    Publication Year: 2006, Page(s): 4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (218 KB) | HTML iconHTML

    Initially, Artificial Evolution focuses on Evolutionary Algorithms handling solutions coded in fixed length structures. In this context, the role of crossover is clearly the mixing of information between solutions. The development of Evolutionary Algorithms operating on structures with variable length, of which genetic programming is one of the most representative instances, opens new questions on... View full abstract»

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  • Particle Swarm Optimization of Feed-Forward Neural Networks with Weight Decay

    Publication Year: 2006, Page(s): 5
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (219 KB) | HTML iconHTML

    Training neural networks is a complex task of great importance in problems of supervised learning. In this work we analyze the use of the Particle Swarm Optimization algorithm and the cooperative variant with the weight decay mechanism for neural network training aiming better generalization performances. For evaluating these algorithms we apply them to benchmark classification problems of the med... View full abstract»

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  • Learning Neural Networks for Visual Servoing Using Evolutionary Methods

    Publication Year: 2006, Page(s): 6
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (154 KB) | HTML iconHTML

    In this article we introduce a method to learn neural networks that solve a visual servoing task. Our method, called EANT, Evolutionary Acquisition of Neural Topologies, starts from a minimal network structure and gradually develops it further using evolutionary reinforcement learning. We have improved EANT by combining it with an optimisation technique called CMA-ES, Covariance Matrix Adaptation ... View full abstract»

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  • Emergence of Information Processor Using Real World--Real-Time Learning of Pursuit Problem

    Publication Year: 2006, Page(s): 7
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (343 KB) | HTML iconHTML

    Real-time reinforcement learning is difficult because number of trials is too much to complete learning within limited time. To solve the problem, we consider reduction of action-state space by information processor using real world without prior knowledge. We obtain the information processor in evolution by setting the fitness as ease of learning. As a typical example, we address pursuit problem ... View full abstract»

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  • On Basic Principles of Intelligent Systems Design

    Publication Year: 2006, Page(s): 8
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (192 KB) | HTML iconHTML

    In the paper we present results of computational experiments to suggest the possibility of a general optimality condition of complex systems: a system demonstrates the optimal performance for a problem, when the structural complexity of the system is in a certain relationship with the structural complexity of the problem. The optimality condition could be used as a basic principle in the design of... View full abstract»

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  • A Comparative Analysis of Data Distribution Methods in an Agent-Based Neural System for Classification Tasks

    Publication Year: 2006, Page(s): 9
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (188 KB) | HTML iconHTML

    The NeurAge (Neural agents) system has been proposed as an alternative to transform the centralized decision making process of a multi-classifier system into a distributed, flexible and incremental one. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant features might be distributed over a set of agen... View full abstract»

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  • Stochastic Differential Portfolio Games with Regime Switching Model

    Publication Year: 2006, Page(s): 10
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (195 KB) | HTML iconHTML

    Stochastic dynamic investment games with regime switching model in continuous time between two investors are developed. The market coefficients are modulated by continuous-time Markov chain. There is a single payoff function which depends on both investors¿ wealth processes. One player chooses a dynamic portfolio strategy in order to maximize this expected payoff, while his opponent is simultaneo... View full abstract»

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  • GNeurAge: An Evolutionary Agent-Based System for Classification Tasks

    Publication Year: 2006, Page(s): 11
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (103 KB) | HTML iconHTML

    The use of intelligent agents in the structure of multiclassifier systems has been investigated in order to overcome some drawbacks of these systems and, as a consequence, to improve the performance of such systems. As a result of this, the NeurAge system was proposed. This system has presented good results in some centralized and distributed classification tasks. In this paper, an investigation o... View full abstract»

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  • Extracting Symbolic Rules from Clustering of Gene Expression Data

    Publication Year: 2006, Page(s): 12
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (161 KB) | HTML iconHTML

    In the last few years, the increasing automation applied to Biology processes has led to a fast accumulation of im- portant biological data. The wide biological implications present in these data makes its analysis unsuitable via con- ventional computing. In this context, Machine Learning (ML) techniques have been showing very promising. One of the ML techniques for analyzing these data is cluster... View full abstract»

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  • Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries

    Publication Year: 2006, Page(s): 13
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (818 KB) | HTML iconHTML

    The paper presents some preliminary results on the brain-gene ontology (BGO) project that is concerned with the collection, presentation and use of knowledge in the form of ontology. BGO includes various concepts, facts, data, software simulators, graphs, videos, animations, and other information forms, related to brain functions, brain diseases, their genetic basis and the relationship between al... View full abstract»

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  • A Novel Microarray Gene Selection Method Based on Consistency

    Publication Year: 2006, Page(s): 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (95 KB) | HTML iconHTML

    Consistency modeling for gene selection is a new topic emerging from recent cancer bioinformatics research. The result of classification or clustering on a training set was often found very different from the same operations on a testing set. Here, we address this issue as a consistency problem. We propose a new concept of performance-based consistency and a new novel gene selection method, Geneti... View full abstract»

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  • Combining Greedy Method and Genetic Algorithm to Identify Transcription Factor Binding Sites

    Publication Year: 2006, Page(s): 15
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (200 KB) | HTML iconHTML

    Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a novel approach to identify transcription factor binding sites. This approach combines greedy method and genetic algorithm (CGGA) to search conserved segment in the given sequence set. A n... View full abstract»

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  • Investigation of a New Artificial Immune System Model Applied to Pattern Recognition

    Publication Year: 2006, Page(s): 16
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (514 KB) | HTML iconHTML

    The discovery of new functionalities through the study of human physiology has contributed toward the evolution of Artificial Immune Systems. The present work investigates a new architecture through observations of natural immunological behavior, for which application to known algorithms contributed toward an improved performance. This paper considers a boarding where the antibodies are grouped in... View full abstract»

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  • RLM: A New Method of Encoding Weights in DNA Strands

    Publication Year: 2006, Page(s): 17
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (182 KB) | HTML iconHTML

    How to encode weights in DNA computing is an important but challenging problem because many practical applications in the real world involve weights. In order to efficiently encode weights in DNA strands, we firstly proposed two definitions, the order number of weight and the relative length graph. And then, by means of the two definitions, we have devised a new method of encoding weights in DNA s... View full abstract»

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  • DNA Computing Model for the 0/1 Knapsack Problem

    Publication Year: 2006, Page(s): 18
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (178 KB) | HTML iconHTML

    We have devised a DNA encoding method and a corresponding DNA algorithm for the 0/1 knapsack problem. Suppose that item set I={1,2 ... n}, profit set P={p_1,p_2,...,p_n}, weight set W={w_1,w_2,...,w_n}, and knapsack capacity is c. We use two DNA strands s_i1 and s_i2 to encode each item i, where the DNA strand s_i1 is with a length of wi whose center part is with a length of p_i, and the DNA stran... View full abstract»

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  • A Contribution to Automatic Design of Image Processing Systems--Breeding Optimized Non-Linear and Oriented Kernels for Texture Analysis

    Publication Year: 2006, Page(s): 19
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (666 KB) | HTML iconHTML

    The rapid development in image processing technology allows the tackling of application of increasing complexity. For efficient design of application specific systems design automation techniques are required. This paper reports on activities for texture classification employing non-linear oriented kernels configured by evolutionary optimization techniques. Our approach was tested with benchmark a... View full abstract»

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