INGENIAS is a methodology for the development of multi-agent systems. INGENIAS support tools has recently incorporated a plug-in called the MTGenerator, which has been developed to facilitate the creation of model tra...
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ISBN:
(纸本)9783642004865
INGENIAS is a methodology for the development of multi-agent systems. INGENIAS support tools has recently incorporated a plug-in called the MTGenerator, which has been developed to facilitate the creation of model transformations by-example from INGENIAS models. The MTGenerator tool overcomes some of the limitations of similar tools about the creation of many-to-many transformation rules. This paper introduces the practical application of the tool to a complete development case study made with INGENIAS, showing the role and benefits of such tools.
This paper describes VisualChord, a Web application, as personal tutor of initiation to the guitar that based on agents architecture that extracts files, tablatures and songs from Internet repositories, normalizing by...
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ISBN:
(纸本)9783642004865
This paper describes VisualChord, a Web application, as personal tutor of initiation to the guitar that based on agents architecture that extracts files, tablatures and songs from Internet repositories, normalizing by rules and with a disambiguation algorithm to be stored in the internal repository with semantic tagging including a difficulty measure for each piece. This allows the user to training with a personalized music pieces selection with his/her guitar. There tries to offer a small personalized and flexible tutor who adapts to the tastes and aptitudes of the user. We describe the VisualChord platform. discuss the architecture, and describe some usability test and results with information about acquiring and making use of this develop.
Three dimensional (3D) shape reconstruction of an object, from its two 2D images, is an important aspect in machine vision applications. Shape from focus (SFF) is a passive optical method for 3D shape recovery in whic...
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ISBN:
(纸本)9783540896180
Three dimensional (3D) shape reconstruction of an object, from its two 2D images, is an important aspect in machine vision applications. Shape from focus (SFF) is a passive optical method for 3D shape recovery in which best-focused points are located among the image sequence. However, existing approaches largely rely on gradient-based sharpness measures and thus are noise sensitive. Moreover, these approaches locally compute focus quality by summing focus values within a window and consequently produce coarse surface. This paper introduces a new SFF method based on bilateral filtering (BF) and principal component analysis (PCA). In the first step, a sequence of neighborhood vectors is convolved with BF and then in the second step, PCA is applied on the resultant matrix to transform data into eigenspace. The score for the first component is employed to compute the depth value. The comparative analysis demonstrates the effectiveness of the proposed method.
In the article there is presented an efficient system for dynamic gesture recognition in movie sequences based on Hidden Markov Models. The system uses colour-based image segmentation methods and introduces high-dimen...
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ISBN:
(纸本)9783642032011
In the article there is presented an efficient system for dynamic gesture recognition in movie sequences based on Hidden Markov Models. The system uses colour-based image segmentation methods and introduces high-dimensional feature vectors to more accurately describe hand shape in the picture. It also utilizes a-priori knowledge on gestures structure in order to allow effective dimensionality reduction, hand posture classification and detection schemes. There is also presented a comparison of the algorithm proposed with competitive methods and argued a particular suitability of the system for the situations when only a small amount of training data is available.
Multi-agent systems may pose a real challenge to management since resources like hosts, agents or agent societies may have different owners and thus different interests. Management tools for multi-agent systems should...
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ISBN:
(纸本)9783642004865
Multi-agent systems may pose a real challenge to management since resources like hosts, agents or agent societies may have different owners and thus different interests. Management tools for multi-agent systems should take into account these inconveniences in order to apply a proper management. We detected in our study that most current management tools only show information about current state. We also think that information about the history of the system can supply a wealth of additional information to system administrators. In this paper we present MAMSY, a management tool for multi-agent systems aimed at showing and controlling current state and past related information.
In the context of the Belief Desire Intention (BDI) agent model and Bratman's theory, intentions play a primary role in reasoning towards actions. Indeed, intentions are supposed to be stable, constrain further de...
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ISBN:
(纸本)9783642004865
In the context of the Belief Desire Intention (BDI) agent model and Bratman's theory, intentions play a primary role in reasoning towards actions. Indeed, intentions are supposed to be stable, constrain further deliberation, be conduct-control ling and influence belief's about the future. Thus, in this paper we present how PRACTIONIST, which is an integrated suite to develop BDI agent systems, embodies such properties of intentions. This allows to develop agents with the ability to know if desires are impossible, incompatible with other intentions and if intentions are achieved or no longer of interest. We first give an overview of the PRACTIONIST deliberation process. Then the implementation of such properties is shown throughout a running example, i.e. the PSTS (PRACTIONIST Stock Trading System), which is aimed to monitor investors stock portfolio by managing risk and profit and supporting decisions for on-line stock trading, on the basis of investors trading rules and their risk attitude.
Molecular simulation docking has become an important contribution to pharmaceutical research. However, in the case of fast screening of many substances (ligands) for their potential impact on a pathogenic protein, com...
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ISBN:
(纸本)9783540896180
Molecular simulation docking has become an important contribution to pharmaceutical research. However, in the case of fast screening of many substances (ligands) for their potential impact on a pathogenic protein, computation time is a serious issue. This paper presents a technique to reduce the search space by keeping the ligands close to the surface of the protein.
This work presents study and experimentation for object recognition when isolated objects are under discussion. The circumstances of similarity transformations, presence of noise, and occlusion have been included as t...
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ISBN:
(纸本)9783540896180
This work presents study and experimentation for object recognition when isolated objects are under discussion. The circumstances of similarity transformations, presence of noise, and occlusion have been included as the part of the study. For simplicity, instead of objects, outlines of the objects have been used for the whole process of the recognition. Moment Descriptors have been used as features of the objects. From the analysis and results using Moment Descriptors, the following questions arise: What is the optimum number of descriptors to be used? Are these descriptors of equal importance? To answer these questions, the problem of selecting the best descriptors has been formulated as an optimization problem. Particle Swarm Optimization technique has been mapped and used successfully to have an object recognition system using minimal number of Moment Descriptors. The proposed method assigns, for each of these descriptors, a weighting factor that reflects the relative importance of that descriptor.
In this paper an adaptive differential evolution algorithm with dynamic changes of population size is presented. In proposed algorithm an adaptive selection of control parameters of the algorithm are introduced. Due t...
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ISBN:
(纸本)9783642032011
In this paper an adaptive differential evolution algorithm with dynamic changes of population size is presented. In proposed algorithm an adaptive selection of control parameters of the algorithm are introduced. Due to these parameters selection, the algorithm gives better results than differential evolution algorithm without this modification. Also, in presented algorithm dynamic changes of population size are introduced. This modification try to overcome limitations connected with premature convergence of the algorithm. Due to dynamic changes of population size, the algorithm can easier get out from local minimum. The proposed algorithm is used to train artificial neural networks. Results obtained are compared with those obtained using: adaptive differential evolution algorithm without dynamic changes of population size, method based on evolutionary algorithm, error back-propagation algorithm, and Levenberg-Marquardt algorithm.
The parameter setting of an algorithm that will result in optimal performance is a tedious task for users who spend a lot of time fine-tuning algorithms for their specific problem domains. This paper presents a multi-...
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ISBN:
(纸本)9783642004865
The parameter setting of an algorithm that will result in optimal performance is a tedious task for users who spend a lot of time fine-tuning algorithms for their specific problem domains. This paper presents a multi-agent tuning system as a framework to set the parameters of a given algorithm which solves a specific problem. Besides, such a configuration is generated taking into account. the current problem instance to be solved. We empirically evaluate our multi-agent tuning system using the configuration of a genetic algorithm applied to the root identification problem. The experimental results show the validity of the proposed model.
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