Rivista e Edizione

Volume 32 (2022): Edizione 2 (June 2022)
Towards Self-Healing Systems through Diagnostics, Fault-Tolerance and Design (Special section, pp. 171-269), Marcin Witczak and Ralf Stetter (Eds.)

Volume 32 (2022): Edizione 1 (March 2022)

Volume 31 (2021): Edizione 4 (December 2021)
Advanced Machine Learning Techniques in Data Analysis (special section, pp. 549-611), Maciej Kusy, Rafał Scherer, and Adam Krzyżak (Eds.)

Volume 31 (2021): Edizione 3 (September 2021)

Volume 31 (2021): Edizione 2 (June 2021)

Volume 31 (2021): Edizione 1 (March 2021)

Volume 30 (2020): Edizione 4 (December 2020)

Volume 30 (2020): Edizione 3 (September 2020)
Big Data and Signal Processing (Special section, pp. 399-473), Joanna Kołodziej, Sabri Pllana, Salvatore Vitabile (Eds.)

Volume 30 (2020): Edizione 2 (June 2020)

Volume 30 (2020): Edizione 1 (March 2020)

Volume 29 (2019): Edizione 4 (December 2019)
New Perspectives in Nonlinear and Intelligent Control (In Honor of Alexander P. Kurdyukov) (special section, pp. 629-712), Julio B. Clempner, Enso Ikonen, Alexander P. Kurdyukov (Eds.)

Volume 29 (2019): Edizione 3 (September 2019)
Information Technology for Systems Research (special section, pp. 427-515), Piotr Kulczycki, Janusz Kacprzyk, László T. Kóczy, Radko Mesiar (Eds.)

Volume 29 (2019): Edizione 2 (June 2019)
Advances in Complex Cloud and Service Oriented Computing (special section, pp. 213-274), Anna Kobusińska, Ching-Hsien Hsu, Kwei-Jay Lin (Eds.)

Volume 29 (2019): Edizione 1 (March 2019)
Exploring Complex and Big Data (special section, pp. 7-91), Johann Gamper, Robert Wrembel (Eds.)

Volume 28 (2018): Edizione 4 (December 2018)

Volume 28 (2018): Edizione 3 (September 2018)

Volume 28 (2018): Edizione 2 (June 2018)
Advanced Diagnosis and Fault-Tolerant Control Methods (special section, pp. 233-333), Vicenç Puig, Dominique Sauter, Christophe Aubrun, Horst Schulte (Eds.)

Volume 28 (2018): Edizione 1 (March 2018)
Ediziones in Parameter Identification and Control (special section, pp. 9-122), Abdel Aitouche (Ed.)

Volume 27 (2017): Edizione 4 (December 2017)

Volume 27 (2017): Edizione 3 (September 2017)
Systems Analysis: Modeling and Control (special section, pp. 457-499), Vyacheslav Maksimov and Boris Mordukhovich (Eds.)

Volume 27 (2017): Edizione 2 (June 2017)

Volume 27 (2017): Edizione 1 (March 2017)

Volume 26 (2016): Edizione 4 (December 2016)

Volume 26 (2016): Edizione 3 (September 2016)

Volume 26 (2016): Edizione 2 (June 2016)

Volume 26 (2016): Edizione 1 (March 2016)

Volume 25 (2015): Edizione 4 (December 2015)
Special issue: Complex Problems in High-Performance Computing Systems, Editors: Mauro Iacono, Joanna Kołodziej

Volume 25 (2015): Edizione 3 (September 2015)

Volume 25 (2015): Edizione 2 (June 2015)

Volume 25 (2015): Edizione 1 (March 2015)
Safety, Fault Diagnosis and Fault Tolerant Control in Aerospace Systems, Silvio Simani, Paolo Castaldi (Eds.)

Volume 24 (2014): Edizione 4 (December 2014)

Volume 24 (2014): Edizione 3 (September 2014)
Modelling and Simulation of High Performance Information Systems (special section, pp. 453-566), Pavel Abaev, Rostislav Razumchik, Joanna Kołodziej (Eds.)

Volume 24 (2014): Edizione 2 (June 2014)
Signals and Systems (special section, pp. 233-312), Ryszard Makowski and Jan Zarzycki (Eds.)

Volume 24 (2014): Edizione 1 (March 2014)
Selected Problems of Biomedical Engineering (special section, pp. 7 - 63), Marek Kowal and Józef Korbicz (Eds.)

Volume 23 (2013): Edizione 4 (December 2013)

Volume 23 (2013): Edizione 3 (September 2013)

Volume 23 (2013): Edizione 2 (June 2013)

Volume 23 (2013): Edizione 1 (March 2013)

Volume 22 (2012): Edizione 4 (December 2012)
Hybrid and Ensemble Methods in Machine Learning (special section, pp. 787 - 881), Oscar Cordón and Przemysław Kazienko (Eds.)

Volume 22 (2012): Edizione 3 (September 2012)

Volume 22 (2012): Edizione 2 (June 2012)
Analysis and Control of Spatiotemporal Dynamic Systems (special section, pp. 245 - 326), Dariusz Uciński and Józef Korbicz (Eds.)

Volume 22 (2012): Edizione 1 (March 2012)
Advances in Control and Fault-Tolerant Systems (special issue), Józef Korbicz, Didier Maquin and Didier Theilliol (Eds.)

Volume 21 (2011): Edizione 4 (December 2011)

Volume 21 (2011): Edizione 3 (September 2011)
Ediziones in Advanced Control and Diagnosis (special section, pp. 423 - 486), Vicenç Puig and Marcin Witczak (Eds.)

Volume 21 (2011): Edizione 2 (June 2011)
Efficient Resource Management for Grid-Enabled Applications (special section, pp. 219 - 306), Joanna Kołodziej and Fatos Xhafa (Eds.)

Volume 21 (2011): Edizione 1 (March 2011)
Semantic Knowledge Engineering (special section, pp. 9 - 95), Grzegorz J. Nalepa and Antoni Ligęza (Eds.)

Volume 20 (2010): Edizione 4 (December 2010)

Volume 20 (2010): Edizione 3 (September 2010)

Volume 20 (2010): Edizione 2 (June 2010)

Volume 20 (2010): Edizione 1 (March 2010)
Computational Intelligence in Modern Control Systems (special section, pp. 7 - 84), Józef Korbicz and Dariusz Uciński (Eds.)

Volume 19 (2009): Edizione 4 (December 2009)
Robot Control Theory (special section, pp. 519 - 588), Cezary Zieliński (Ed.)

Volume 19 (2009): Edizione 3 (September 2009)
Verified Methods: Applications in Medicine and Engineering (special issue), Andreas Rauh, Ekaterina Auer, Eberhard P. Hofer and Wolfram Luther (Eds.)

Volume 19 (2009): Edizione 2 (June 2009)

Volume 19 (2009): Edizione 1 (March 2009)

Volume 18 (2008): Edizione 4 (December 2008)
Ediziones in Fault Diagnosis and Fault Tolerant Control (special issue), Józef Korbicz and Dominique Sauter (Eds.)

Volume 18 (2008): Edizione 3 (September 2008)
Selected Problems of Computer Science and Control (special issue), Krzysztof Gałkowski, Eric Rogers and Jan Willems (Eds.)

Volume 18 (2008): Edizione 2 (June 2008)
Selected Topics in Biological Cybernetics (special section, pp. 117 - 170), Andrzej Kasiński and Filip Ponulak (Eds.)

Volume 18 (2008): Edizione 1 (March 2008)
Applied Image Processing (special issue), Anton Kummert and Ewaryst Rafajłowicz (Eds.)

Volume 17 (2007): Edizione 4 (December 2007)

Volume 17 (2007): Edizione 3 (September 2007)
Scientific Computation for Fluid Mechanics and Hyperbolic Systems (special issue), Jan Sokołowski and Eric Sonnendrücker (Eds.)

Volume 17 (2007): Edizione 2 (June 2007)

Volume 17 (2007): Edizione 1 (March 2007)

Dettagli della rivista
Formato
Rivista
eISSN
2083-8492
Pubblicato per la prima volta
05 Apr 2007
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

Volume 25 (2015): Edizione 3 (September 2015)

Dettagli della rivista
Formato
Rivista
eISSN
2083-8492
Pubblicato per la prima volta
05 Apr 2007
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

18 Articoli

Special Section Title: Agents in Intelligent Computing and Simulation Systems, Editors: Aleksander Byrski, Marek Kisiel-Dorohinicki, Grzegorz Dobrowolski

Accesso libero

A situation-based multi-agent architecture for handling misunderstandings in interactions

Pubblicato online: 30 Sep 2015
Pagine: 439 - 454

Astratto

Abstract

During interactions, system actors may face up misunderstandings when their local states contain inconsistent data about the same fact. Misunderstandings in interactions are likely to reduce interactivity performances (deviation or deadlock) or even affect overall system behavior. In this paper, we characterize misunderstandings in interactions between system actors (that may be human users or system agents) in interactive adaptive systems. To deal with such misunderstandings and ensure state consistency, we present an agent-based architecture and a scenario structuring approach. The system includes several agents devoted to scenario unfolding, plot adaptation and consistency management. Scenario structuring is based on the notion of a situation that is an elementary building block dividing the interactions between systems’ actors into contextual scenes. This pattern supports not only scenario execution but consistency management as well. In order to organize and control interactions, the situation contextualizes interactions and activity of the system’s actors. It also includes prevention and tolerance agent-based mechanisms to deal with the misunderstandings and their causes. We validate our consistency management mechanisms using Uppaal simulation and provide some experimental results to show the effectiveness of our approach on an online distance learning case study

Keywords

  • interactive adaptive systems
  • misunderstandings in interactions
  • situation structuring
  • consistency management
Accesso libero

A belief revision approach for argumentation-based negotiation agents

Pubblicato online: 30 Sep 2015
Pagine: 455 - 470

Astratto

Abstract

Negotiation is an interaction that happens in multi-agent systems when agents have conflicting objectives and must look for an acceptable agreement. A typical negotiating situation involves two agents that cannot reach their goals by themselves because they do not have some resources they need or they do not know how to use them to reach their goals. Therefore, they must start a negotiation dialogue, taking also into account that they might have incomplete or wrong beliefs about the other agent’s goals and resources. This article presents a negotiating agent model based on argumentation, which is used by the agents to reason on how to exchange resources and knowledge in order to achieve their goals. Agents that negotiate have incomplete beliefs about the others, so that the exchange of arguments gives them information that makes it possible to update their beliefs. In order to formalize their proposals in a negotiation setting, the agents must be able to generate, select and evaluate arguments associated with such offers, updating their mental state accordingly. In our approach, we will focus on an argumentation-based negotiation model between two cooperative agents. The arguments generation and interpretation process is based on belief change operations (expansions, contractions and revisions), and the selection process is a based on a strategy. This approach is presented through a high-level algorithm implemented in logic programming. We show various theoretical properties associated with this approach, which have been formalized and proved using Coq, a formal proof management system. We also illustrate, through a case study, the applicability of our approach in order to solve a slightly modified version of the well-known home improvement agents problem. Moreover, we present various simulations that allow assessing the impact of belief revision on the negotiation process.

Keywords

  • argumentation-based negotiation
  • collaborative agents
  • belief revision
  • multi-agent system
Accesso libero

A strategy learning model for autonomous agents based on classification

Pubblicato online: 30 Sep 2015
Pagine: 471 - 482

Astratto

Abstract

In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

Keywords

  • autonomous agents
  • strategy learning
  • supervised learning
  • classification
  • reinforcement learning
Accesso libero

An agent-oriented hierarchic strategy for solving inverse problems

Pubblicato online: 30 Sep 2015
Pagine: 483 - 498

Astratto

Abstract

The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainly because the direct solver accuracy (performed by the hp-adaptive finite element method) is dynamically adjusted for each inverse search step. The computational cost is further decreased by the strategy employed for solution inter-processing and fitness deterioration. The HMS efficiency is compared with the results of a standard evolutionary technique, as well as with the multi-start strategy on benchmarks that exhibit typical inverse problems’ difficulties. Finally, an HMS application to a real-life engineering problem leading to the identification of oil deposits by inverting magnetotelluric measurements is presented. The HMS applicability to the inversion of magnetotelluric data is also mathematically verified.

Keywords

  • inverse problems
  • hybrid optimization methods
  • memetic algorithms
  • multi-agent systems
  • magnetotelluric data inversion
Accesso libero

A study on meme propagation in multimemetic algorithms

Pubblicato online: 30 Sep 2015
Pagine: 499 - 512

Astratto

Abstract

Multimemetic algorithms (MMAs) are a subclass of memetic algorithms in which memes are explicitly attached to genotypes and evolve alongside them. We analyze the propagation of memes in MMAs with a spatial structure. For this purpose we propose an idealized selecto-Lamarckian model that only features selection and local improvement, and study under which conditions good, high-potential memes can proliferate. We compare population models with panmictic and toroidal grid topologies. We show that the increased takeover time induced by the latter is essential for improving the chances for good memes to express themselves in the population by improving their hosts, hence enhancing their survival rates. Experiments realized with an actual MMA on three different complex pseudo-Boolean functions are consistent with these findings, indicating that memes are more successful in a spatially structured MMA, rather than in a panmictic MMA, and that the performance of the former is significantly better than that of its panmictic counterpart

Keywords

  • memetic algorithms
  • spatial structure
  • meme propagation
Accesso libero

A multi-agent brokerage platform for media content recommendation

Pubblicato online: 30 Sep 2015
Pagine: 513 - 527

Astratto

Abstract

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

Keywords

  • multi-agent computing
  • brokerage platform
  • media content personalisation
  • recommendation.
Accesso libero

A sixth-order finite volume method for the 1D biharmonic operator: Application to intramedullary nail simulation

Pubblicato online: 30 Sep 2015
Pagine: 529 - 537

Astratto

Abstract

A new very high-order finite volume method to solve problems with harmonic and biharmonic operators for onedimensional geometries is proposed. The main ingredient is polynomial reconstruction based on local interpolations of mean values providing accurate approximations of the solution up to the sixth-order accuracy. First developed with the harmonic operator, an extension for the biharmonic operator is obtained, which allows designing a very high-order finite volume scheme where the solution is obtained by solving a matrix-free problem. An application in elasticity coupling the two operators is presented. We consider a beam subject to a combination of tensile and bending loads, where the main goal is the stress critical point determination for an intramedullary nail.

Keywords

  • finite volume method
  • polynomial reconstruction operator
  • harmonic operator
  • biharmonic operator
  • high-order method
Accesso libero

Analysis of the descriptor Roesser model with the use of the Drazin inverse

Pubblicato online: 30 Sep 2015
Pagine: 539 - 546

Astratto

Abstract

A method of analysis for a class of descriptor 2D discrete-time linear systems described by the Roesser model with a regular pencil is proposed. The method is based on the transformation of the model to a special form with the use of elementary row and column operations and on the application of a Drazin inverse of matrices to handle the model. The method is illustrated with a numerical example

Keywords

  • Drazin inverse
  • descriptor
  • Roesser model
  • descriptor-time
  • 2D linear system
Accesso libero

An H sliding mode observer for Takagi–Sugeno nonlinear systems with simultaneous actuator and sensor faults An

Pubblicato online: 30 Sep 2015
Pagine: 547 - 559

Astratto

Abstract

This paper considers the problem of robust reconstruction of simultaneous actuator and sensor faults for a class of uncertain Takagi-Sugeno nonlinear systems with unmeasurable premise variables. The proposed fault reconstruction and estimation design method with H performance is used to reconstruct both actuator and sensor faults when the latter are transformed into pseudo-actuator faults by introducing a simple filter. The main contribution is to develop a sliding mode observer (SMO) with two discontinuous terms to solve the problem of simultaneous faults. Sufficient stability conditions in terms linear matrix inequalities are achieved to guarantee the stability of the state estimation error. The observer gains are obtained by solving a convex multiobjective optimization problem. Simulation examples are given to illustrate the performance of the proposed observer

Keywords

  • fault reconstruction and estimation
  • simultaneous faults
  • H∞ sliding mode observer
  • uncertain Takagi-Sugeno systems
  • LMI optimization
Accesso libero

Design of passive fault-tolerant controllers of a quadrotor based on sliding mode theory

Pubblicato online: 30 Sep 2015
Pagine: 561 - 576

Astratto

Keywords

  • quadrotor UAV control
  • fault tolerant control
  • sliding mode control
  • cascaded SMC
  • bio-inspired gain tuning
Accesso libero

A symbolic shortest path algorithm for computing subgame-perfect Nash equilibria

Pubblicato online: 30 Sep 2015
Pagine: 577 - 596

Astratto

Abstract

Consider games where players wish to minimize the cost to reach some state. A subgame-perfect Nash equilibrium can be regarded as a collection of optimal paths on such games. Similarly, the well-known state-labeling algorithm used in model checking can be viewed as computing optimal paths on a Kripke structure, where each path has a minimum number of transitions. We exploit these similarities in a common generalization of extensive games and Kripke structures that we name “graph games”. By extending the Bellman-Ford algorithm for computing shortest paths, we obtain a model-checking algorithm for graph games with respect to formulas in an appropriate logic. Hence, when given a certain formula, our model-checking algorithm computes the subgame-perfect Nash equilibrium (as opposed to simply determining whether or not a given collection of paths is a Nash equilibrium). Next, we develop a symbolic version of our model checker allowing us to handle larger graph games. We illustrate our formalism on the critical-path method as well as games with perfect information. Finally, we report on the execution time of benchmarks of an implementation of our algorithms

Keywords

  • shortest path
  • Bellman-Ford
  • Nash equilibrium
  • BDD
  • model checking
Accesso libero

Bottom-up learning of hierarchical models in a class of deterministic POMDP environments

Pubblicato online: 30 Sep 2015
Pagine: 597 - 615

Astratto

Abstract

The theory of partially observable Markov decision processes (POMDPs) is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden Markov models and neural networks. However, little attention has been paid to bottom-up approaches for learning POMDP models. In this paper, we present a novel bottom-up learning algorithm for hierarchical POMDP models and prove that, by using this algorithm, a perfect model (i.e., a model that can perfectly predict future observations) can be learned at least in a class of deterministic POMDP environments

Keywords

  • partially observable Markov decision processes
  • hierarchical models
  • bottom-up learning
Accesso libero

A repeated imitation model with dependence between stages: Decision strategies and rewards

Pubblicato online: 30 Sep 2015
Pagine: 617 - 630

Astratto

Abstract

Adversarial decision making is aimed at determining strategies to anticipate the behavior of an opponent trying to learn from our actions. One defense is to make decisions intended to confuse the opponent, although our rewards can be diminished. This idea has already been captured in an adversarial model introduced in a previous work, in which two agents separately issue responses to an unknown sequence of external inputs. Each agent’s reward depends on the current input and the responses of both agents. In this contribution, (a) we extend the original model by establishing stochastic dependence between an agent’s responses and the next input of the sequence, and (b) we study the design of time varying decision strategies for the extended model. The strategies obtained are compared against static strategies from theoretical and empirical points of view. The results show that time varying strategies outperform static ones

Keywords

  • adversarial decision making
  • imitation
  • strategies
  • state dependence
  • reward
Accesso libero

Acoustic analysis assessment in speech pathology detection

Pubblicato online: 30 Sep 2015
Pagine: 631 - 643

Astratto

Abstract

Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients. In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis (PCA), kernel principal component analysis (kPCA) and an auto-associative neural network (NLPCA) in four kinds of pathology detection (hyperfunctional dysphonia, functional dysphonia, laryngitis, vocal cord paralysis) using the a, i and u vowels, spoken at a high, low and normal pitch. The results indicate that the kPCA and NLPCA methods can be considered a step towards pathology detection of the vocal folds. The results show that such an approach provides acceptable results for this purpose, with the best efficiency levels of around 100%. The study brings the most commonly used approaches to speech signal processing together and leads to a comparison of the machine learning methods determining the health status of the patient

Keywords

  • linear PCA
  • non-linear PCA
  • auto-associative neural network
  • validation
  • voice pathology detection
Accesso libero

On the order equivalence relation of binary association measures

Pubblicato online: 30 Sep 2015
Pagine: 645 - 657

Astratto

Abstract

Over a century of research has resulted in a set of more than a hundred binary association measures. Many of them share similar properties. An overview of binary association measures is presented, focused on their order equivalences. Association measures are grouped according to their relations. Transformations between these measures are shown, both formally and visually. A generalization coefficient is proposed, based on joint probability and marginal probabilities. Combining association measures is one of recent trends in computer science. Measures are combined in linear and nonlinear discrimination models, automated feature selection or construction. Knowledge about their relations is particularly important to avoid problems of meaningless results, zeroed generalized variances, the curse of dimensionality, or simply to save time

Keywords

  • association coefficient
  • result ranking
  • linear combination
  • zeroed variance determinant
  • feature selection
Accesso libero

Signature verification: A comprehensive study of the hidden signature method

Pubblicato online: 30 Sep 2015
Pagine: 659 - 674

Astratto

Abstract

Many handwritten signature verification algorithms have been developed in order to distinguish between genuine signatures and forgeries. An important group of these methods is based on dynamic time warping (DTW). Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures. The right selection of template signatures has a big impact on that verification. In this article, we describe our proposition for replacing the template signatures with the hidden signature-an artificial signature which is created by minimizing the mean misalignment between itself and the signatures from the enrollment set. We present a few hidden signature estimation methods together with their comprehensive comparison. The hidden signature opens a number of new possibilities for signature analysis. We apply statistical properties of the hidden signature to normalize the error signal of the verified signature and to use the misalignment on the normalized errors as a verification basis. A result, we achieve satisfying error rates that allow creating an on-line system, ready for operating in a real-world environment

Keywords

  • verification
  • on-line recognition
  • time warping
  • hidden signature
Accesso libero

Computing with words with the use of inverse RDM models of membership functions

Pubblicato online: 30 Sep 2015
Pagine: 675 - 688

Astratto

Abstract

Computing with words is a way to artificial, human-like thinking. The paper shows some new possibilities of solving difficult problems of computing with words which are offered by relative-distance-measure RDM models of fuzzy membership functions. Such models are based on RDM interval arithmetic. The way of calculation with words was shown using a specific problem of flight delay formulated by Lotfi Zadeh. The problem seems easy at first sight, but according to the authors’ knowledge it has not been solved yet. Results produced with the achieved solution were tested. The investigations also showed that computing with words sometimes offers possibilities of achieving better problem solutions than with the human mind.

Keywords

  • computing with words
  • fuzzy arithmetic
  • RDM fuzzy arithmetic
  • granular computing
Accesso libero

Building the library of RNA 3D nucleotide conformations using the clustering approach

Pubblicato online: 30 Sep 2015
Pagine: 689 - 700

Astratto

Abstract

An increasing number of known RNA 3D structures contributes to the recognition of various RNA families and identification of their features. These tasks are based on an analysis of RNA conformations conducted at different levels of detail. On the other hand, the knowledge of native nucleotide conformations is crucial for structure prediction and understanding of RNA folding. However, this knowledge is stored in structural databases in a rather distributed form. Therefore, only automated methods for sampling the space of RNA structures can reveal plausible conformational representatives useful for further analysis. Here, we present a machine learning-based approach to inspect the dataset of RNA three-dimensional structures and to create a library of nucleotide conformers. A median neural gas algorithm is applied to cluster nucleotide structures upon their trigonometric description. The clustering procedure is two-stage: (i) backbone- and (ii) ribose-driven. We show the resulting library that contains RNA nucleotide representatives over the entire data, and we evaluate its quality by computing normal distribution measures and average RMSD between data points as well as the prototype within each cluster.

Keywords

  • RNA nucleotides
  • conformer library
  • torsion angles
  • clustering
  • neural gas
18 Articoli

Special Section Title: Agents in Intelligent Computing and Simulation Systems, Editors: Aleksander Byrski, Marek Kisiel-Dorohinicki, Grzegorz Dobrowolski

Accesso libero

A situation-based multi-agent architecture for handling misunderstandings in interactions

Pubblicato online: 30 Sep 2015
Pagine: 439 - 454

Astratto

Abstract

During interactions, system actors may face up misunderstandings when their local states contain inconsistent data about the same fact. Misunderstandings in interactions are likely to reduce interactivity performances (deviation or deadlock) or even affect overall system behavior. In this paper, we characterize misunderstandings in interactions between system actors (that may be human users or system agents) in interactive adaptive systems. To deal with such misunderstandings and ensure state consistency, we present an agent-based architecture and a scenario structuring approach. The system includes several agents devoted to scenario unfolding, plot adaptation and consistency management. Scenario structuring is based on the notion of a situation that is an elementary building block dividing the interactions between systems’ actors into contextual scenes. This pattern supports not only scenario execution but consistency management as well. In order to organize and control interactions, the situation contextualizes interactions and activity of the system’s actors. It also includes prevention and tolerance agent-based mechanisms to deal with the misunderstandings and their causes. We validate our consistency management mechanisms using Uppaal simulation and provide some experimental results to show the effectiveness of our approach on an online distance learning case study

Keywords

  • interactive adaptive systems
  • misunderstandings in interactions
  • situation structuring
  • consistency management
Accesso libero

A belief revision approach for argumentation-based negotiation agents

Pubblicato online: 30 Sep 2015
Pagine: 455 - 470

Astratto

Abstract

Negotiation is an interaction that happens in multi-agent systems when agents have conflicting objectives and must look for an acceptable agreement. A typical negotiating situation involves two agents that cannot reach their goals by themselves because they do not have some resources they need or they do not know how to use them to reach their goals. Therefore, they must start a negotiation dialogue, taking also into account that they might have incomplete or wrong beliefs about the other agent’s goals and resources. This article presents a negotiating agent model based on argumentation, which is used by the agents to reason on how to exchange resources and knowledge in order to achieve their goals. Agents that negotiate have incomplete beliefs about the others, so that the exchange of arguments gives them information that makes it possible to update their beliefs. In order to formalize their proposals in a negotiation setting, the agents must be able to generate, select and evaluate arguments associated with such offers, updating their mental state accordingly. In our approach, we will focus on an argumentation-based negotiation model between two cooperative agents. The arguments generation and interpretation process is based on belief change operations (expansions, contractions and revisions), and the selection process is a based on a strategy. This approach is presented through a high-level algorithm implemented in logic programming. We show various theoretical properties associated with this approach, which have been formalized and proved using Coq, a formal proof management system. We also illustrate, through a case study, the applicability of our approach in order to solve a slightly modified version of the well-known home improvement agents problem. Moreover, we present various simulations that allow assessing the impact of belief revision on the negotiation process.

Keywords

  • argumentation-based negotiation
  • collaborative agents
  • belief revision
  • multi-agent system
Accesso libero

A strategy learning model for autonomous agents based on classification

Pubblicato online: 30 Sep 2015
Pagine: 471 - 482

Astratto

Abstract

In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

Keywords

  • autonomous agents
  • strategy learning
  • supervised learning
  • classification
  • reinforcement learning
Accesso libero

An agent-oriented hierarchic strategy for solving inverse problems

Pubblicato online: 30 Sep 2015
Pagine: 483 - 498

Astratto

Abstract

The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainly because the direct solver accuracy (performed by the hp-adaptive finite element method) is dynamically adjusted for each inverse search step. The computational cost is further decreased by the strategy employed for solution inter-processing and fitness deterioration. The HMS efficiency is compared with the results of a standard evolutionary technique, as well as with the multi-start strategy on benchmarks that exhibit typical inverse problems’ difficulties. Finally, an HMS application to a real-life engineering problem leading to the identification of oil deposits by inverting magnetotelluric measurements is presented. The HMS applicability to the inversion of magnetotelluric data is also mathematically verified.

Keywords

  • inverse problems
  • hybrid optimization methods
  • memetic algorithms
  • multi-agent systems
  • magnetotelluric data inversion
Accesso libero

A study on meme propagation in multimemetic algorithms

Pubblicato online: 30 Sep 2015
Pagine: 499 - 512

Astratto

Abstract

Multimemetic algorithms (MMAs) are a subclass of memetic algorithms in which memes are explicitly attached to genotypes and evolve alongside them. We analyze the propagation of memes in MMAs with a spatial structure. For this purpose we propose an idealized selecto-Lamarckian model that only features selection and local improvement, and study under which conditions good, high-potential memes can proliferate. We compare population models with panmictic and toroidal grid topologies. We show that the increased takeover time induced by the latter is essential for improving the chances for good memes to express themselves in the population by improving their hosts, hence enhancing their survival rates. Experiments realized with an actual MMA on three different complex pseudo-Boolean functions are consistent with these findings, indicating that memes are more successful in a spatially structured MMA, rather than in a panmictic MMA, and that the performance of the former is significantly better than that of its panmictic counterpart

Keywords

  • memetic algorithms
  • spatial structure
  • meme propagation
Accesso libero

A multi-agent brokerage platform for media content recommendation

Pubblicato online: 30 Sep 2015
Pagine: 513 - 527

Astratto

Abstract

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

Keywords

  • multi-agent computing
  • brokerage platform
  • media content personalisation
  • recommendation.
Accesso libero

A sixth-order finite volume method for the 1D biharmonic operator: Application to intramedullary nail simulation

Pubblicato online: 30 Sep 2015
Pagine: 529 - 537

Astratto

Abstract

A new very high-order finite volume method to solve problems with harmonic and biharmonic operators for onedimensional geometries is proposed. The main ingredient is polynomial reconstruction based on local interpolations of mean values providing accurate approximations of the solution up to the sixth-order accuracy. First developed with the harmonic operator, an extension for the biharmonic operator is obtained, which allows designing a very high-order finite volume scheme where the solution is obtained by solving a matrix-free problem. An application in elasticity coupling the two operators is presented. We consider a beam subject to a combination of tensile and bending loads, where the main goal is the stress critical point determination for an intramedullary nail.

Keywords

  • finite volume method
  • polynomial reconstruction operator
  • harmonic operator
  • biharmonic operator
  • high-order method
Accesso libero

Analysis of the descriptor Roesser model with the use of the Drazin inverse

Pubblicato online: 30 Sep 2015
Pagine: 539 - 546

Astratto

Abstract

A method of analysis for a class of descriptor 2D discrete-time linear systems described by the Roesser model with a regular pencil is proposed. The method is based on the transformation of the model to a special form with the use of elementary row and column operations and on the application of a Drazin inverse of matrices to handle the model. The method is illustrated with a numerical example

Keywords

  • Drazin inverse
  • descriptor
  • Roesser model
  • descriptor-time
  • 2D linear system
Accesso libero

An H sliding mode observer for Takagi–Sugeno nonlinear systems with simultaneous actuator and sensor faults An

Pubblicato online: 30 Sep 2015
Pagine: 547 - 559

Astratto

Abstract

This paper considers the problem of robust reconstruction of simultaneous actuator and sensor faults for a class of uncertain Takagi-Sugeno nonlinear systems with unmeasurable premise variables. The proposed fault reconstruction and estimation design method with H performance is used to reconstruct both actuator and sensor faults when the latter are transformed into pseudo-actuator faults by introducing a simple filter. The main contribution is to develop a sliding mode observer (SMO) with two discontinuous terms to solve the problem of simultaneous faults. Sufficient stability conditions in terms linear matrix inequalities are achieved to guarantee the stability of the state estimation error. The observer gains are obtained by solving a convex multiobjective optimization problem. Simulation examples are given to illustrate the performance of the proposed observer

Keywords

  • fault reconstruction and estimation
  • simultaneous faults
  • H∞ sliding mode observer
  • uncertain Takagi-Sugeno systems
  • LMI optimization
Accesso libero

Design of passive fault-tolerant controllers of a quadrotor based on sliding mode theory

Pubblicato online: 30 Sep 2015
Pagine: 561 - 576

Astratto

Keywords

  • quadrotor UAV control
  • fault tolerant control
  • sliding mode control
  • cascaded SMC
  • bio-inspired gain tuning
Accesso libero

A symbolic shortest path algorithm for computing subgame-perfect Nash equilibria

Pubblicato online: 30 Sep 2015
Pagine: 577 - 596

Astratto

Abstract

Consider games where players wish to minimize the cost to reach some state. A subgame-perfect Nash equilibrium can be regarded as a collection of optimal paths on such games. Similarly, the well-known state-labeling algorithm used in model checking can be viewed as computing optimal paths on a Kripke structure, where each path has a minimum number of transitions. We exploit these similarities in a common generalization of extensive games and Kripke structures that we name “graph games”. By extending the Bellman-Ford algorithm for computing shortest paths, we obtain a model-checking algorithm for graph games with respect to formulas in an appropriate logic. Hence, when given a certain formula, our model-checking algorithm computes the subgame-perfect Nash equilibrium (as opposed to simply determining whether or not a given collection of paths is a Nash equilibrium). Next, we develop a symbolic version of our model checker allowing us to handle larger graph games. We illustrate our formalism on the critical-path method as well as games with perfect information. Finally, we report on the execution time of benchmarks of an implementation of our algorithms

Keywords

  • shortest path
  • Bellman-Ford
  • Nash equilibrium
  • BDD
  • model checking
Accesso libero

Bottom-up learning of hierarchical models in a class of deterministic POMDP environments

Pubblicato online: 30 Sep 2015
Pagine: 597 - 615

Astratto

Abstract

The theory of partially observable Markov decision processes (POMDPs) is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden Markov models and neural networks. However, little attention has been paid to bottom-up approaches for learning POMDP models. In this paper, we present a novel bottom-up learning algorithm for hierarchical POMDP models and prove that, by using this algorithm, a perfect model (i.e., a model that can perfectly predict future observations) can be learned at least in a class of deterministic POMDP environments

Keywords

  • partially observable Markov decision processes
  • hierarchical models
  • bottom-up learning
Accesso libero

A repeated imitation model with dependence between stages: Decision strategies and rewards

Pubblicato online: 30 Sep 2015
Pagine: 617 - 630

Astratto

Abstract

Adversarial decision making is aimed at determining strategies to anticipate the behavior of an opponent trying to learn from our actions. One defense is to make decisions intended to confuse the opponent, although our rewards can be diminished. This idea has already been captured in an adversarial model introduced in a previous work, in which two agents separately issue responses to an unknown sequence of external inputs. Each agent’s reward depends on the current input and the responses of both agents. In this contribution, (a) we extend the original model by establishing stochastic dependence between an agent’s responses and the next input of the sequence, and (b) we study the design of time varying decision strategies for the extended model. The strategies obtained are compared against static strategies from theoretical and empirical points of view. The results show that time varying strategies outperform static ones

Keywords

  • adversarial decision making
  • imitation
  • strategies
  • state dependence
  • reward
Accesso libero

Acoustic analysis assessment in speech pathology detection

Pubblicato online: 30 Sep 2015
Pagine: 631 - 643

Astratto

Abstract

Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients. In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis (PCA), kernel principal component analysis (kPCA) and an auto-associative neural network (NLPCA) in four kinds of pathology detection (hyperfunctional dysphonia, functional dysphonia, laryngitis, vocal cord paralysis) using the a, i and u vowels, spoken at a high, low and normal pitch. The results indicate that the kPCA and NLPCA methods can be considered a step towards pathology detection of the vocal folds. The results show that such an approach provides acceptable results for this purpose, with the best efficiency levels of around 100%. The study brings the most commonly used approaches to speech signal processing together and leads to a comparison of the machine learning methods determining the health status of the patient

Keywords

  • linear PCA
  • non-linear PCA
  • auto-associative neural network
  • validation
  • voice pathology detection
Accesso libero

On the order equivalence relation of binary association measures

Pubblicato online: 30 Sep 2015
Pagine: 645 - 657

Astratto

Abstract

Over a century of research has resulted in a set of more than a hundred binary association measures. Many of them share similar properties. An overview of binary association measures is presented, focused on their order equivalences. Association measures are grouped according to their relations. Transformations between these measures are shown, both formally and visually. A generalization coefficient is proposed, based on joint probability and marginal probabilities. Combining association measures is one of recent trends in computer science. Measures are combined in linear and nonlinear discrimination models, automated feature selection or construction. Knowledge about their relations is particularly important to avoid problems of meaningless results, zeroed generalized variances, the curse of dimensionality, or simply to save time

Keywords

  • association coefficient
  • result ranking
  • linear combination
  • zeroed variance determinant
  • feature selection
Accesso libero

Signature verification: A comprehensive study of the hidden signature method

Pubblicato online: 30 Sep 2015
Pagine: 659 - 674

Astratto

Abstract

Many handwritten signature verification algorithms have been developed in order to distinguish between genuine signatures and forgeries. An important group of these methods is based on dynamic time warping (DTW). Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures. The right selection of template signatures has a big impact on that verification. In this article, we describe our proposition for replacing the template signatures with the hidden signature-an artificial signature which is created by minimizing the mean misalignment between itself and the signatures from the enrollment set. We present a few hidden signature estimation methods together with their comprehensive comparison. The hidden signature opens a number of new possibilities for signature analysis. We apply statistical properties of the hidden signature to normalize the error signal of the verified signature and to use the misalignment on the normalized errors as a verification basis. A result, we achieve satisfying error rates that allow creating an on-line system, ready for operating in a real-world environment

Keywords

  • verification
  • on-line recognition
  • time warping
  • hidden signature
Accesso libero

Computing with words with the use of inverse RDM models of membership functions

Pubblicato online: 30 Sep 2015
Pagine: 675 - 688

Astratto

Abstract

Computing with words is a way to artificial, human-like thinking. The paper shows some new possibilities of solving difficult problems of computing with words which are offered by relative-distance-measure RDM models of fuzzy membership functions. Such models are based on RDM interval arithmetic. The way of calculation with words was shown using a specific problem of flight delay formulated by Lotfi Zadeh. The problem seems easy at first sight, but according to the authors’ knowledge it has not been solved yet. Results produced with the achieved solution were tested. The investigations also showed that computing with words sometimes offers possibilities of achieving better problem solutions than with the human mind.

Keywords

  • computing with words
  • fuzzy arithmetic
  • RDM fuzzy arithmetic
  • granular computing
Accesso libero

Building the library of RNA 3D nucleotide conformations using the clustering approach

Pubblicato online: 30 Sep 2015
Pagine: 689 - 700

Astratto

Abstract

An increasing number of known RNA 3D structures contributes to the recognition of various RNA families and identification of their features. These tasks are based on an analysis of RNA conformations conducted at different levels of detail. On the other hand, the knowledge of native nucleotide conformations is crucial for structure prediction and understanding of RNA folding. However, this knowledge is stored in structural databases in a rather distributed form. Therefore, only automated methods for sampling the space of RNA structures can reveal plausible conformational representatives useful for further analysis. Here, we present a machine learning-based approach to inspect the dataset of RNA three-dimensional structures and to create a library of nucleotide conformers. A median neural gas algorithm is applied to cluster nucleotide structures upon their trigonometric description. The clustering procedure is two-stage: (i) backbone- and (ii) ribose-driven. We show the resulting library that contains RNA nucleotide representatives over the entire data, and we evaluate its quality by computing normal distribution measures and average RMSD between data points as well as the prototype within each cluster.

Keywords

  • RNA nucleotides
  • conformer library
  • torsion angles
  • clustering
  • neural gas

Pianifica la tua conferenza remota con Sciendo