Catálogo de publicaciones - libros

In the paper the idea of an immunological selection mechanism for the agent-based evolutionary computation is presented. General considerations are illustrated by the particular system dedicated to function optimization. Selected experimental results allow for the comparison of the performance of immune-inpired selection mechanisms and classical energetic ones.

This article presents a discussion about security mechanisms in agent and multiagent systems. Presented discussion focuses on the design of an artificial immune system for intrusion detection in agent systems. An immunological approach to change detection seems very useful in design of security mechanisms for an agent functioning in his environment. Reasons for this expectation are the principles of a computer immune system such as distribution and autonomy. Mentioned principles of artificial immune systems are strongly connected with main principles of agent technology which are the autonomy of an agent and distribution in the case of multiagent system.

In this paper, the methodology of generating images of melanocytic skin lesions is briefly outlined. The developed methodology proceeds essentially in two steps. In the first one, semantic description of skin lesions of anonymous patients is carefully analyzed to catch important features (symptoms) and to mine their logical values. Then, data gained in this step are used to control a specific simulation process, in which the simulated lesion’s image is randomly put together from pre-defined fragments (textures). In this way, a single textual vector representing a distinct lesion, can produce a collection of several images of a given category. The quality of simulated images, verified by an independent expert was found to be quite satisfactory.

Using electronic mail (e-mail) we can communicate freely and almost at no cost. It creates new possibilities for companies that can use e-mail to send advertisements to their clients (that is called direct-mailing). The term spam refers mostly to that kind of advertisements. Massively sent unsolicited e-mails attack many Internet users. Unfortunately, this kind of message can not be filtered out by simple rule-based filters. In this paper we will extend artificial immune system (AIS) proposed in [6] which is based on mammalian immune system and designed to protect users from spam. Generally AIS are also used to detect computer viruses or to detect anomalies in computer networks.

Mammalian immune system and especially clonal selection principle, responsible for coping with external intruders, is an inspiration for a set of heuristic optimization algorithms. Below, a few of them are compared on a set of nonstationary optimization benchmarks. One of the algorithms is our proposal, called AIIA (Artificial Immune Iterated Algorithm). We compare two versions of this algorithm with two other well known algorithms. The results show that all the algorithms based on clonal selection principle can be quite efficient tools for nonstationary optimization.

The simple genetic algorithm (SGA) and its convergence analysis are main subjects of the article. The SGA is defined on a finite multi-set of potential problem solutions (individuals) together with random mutation and selection operators. The selection operation acts on the basis of the fitness function defined on potential solutions (individuals), and is fundamental for the problem considered. Generation of a new population from the given one, is realized by the iterative actions of those operators. Each iteration is written in the form of a transition operator acting on probability vectors which describe probability distributions of each population. The transition operator is a Markov one. Thanks to the well-developed theory of Markov operators [5,8,9] new conditions for stability of the transition operator are formulated. The obtained results are related to the class of genetic operators and are not restricted to binary operators.

This paper proposes a new evolutionary algorithm (EA) which includes five different mutation operators: nodes merging, nodes deletion, penalizing, nodes inserting and hybrid training. The algorithm adaptively determines the structure and parameters of the radial basis function neural networks (RBFN). Many different radial basis functions with different sizes (covering area, locations and orientations) were used to construct the near-optimal RBFN during training. The resulting RBFN behaves even more powerful and requires fewer nodes than other algorithms. Simulation results in face recognition show that the system achieves excellent performance both in terms of error rates of classification and learning efficiency.

The paper presents the GAVis (Genetic Algorithm Visualization) system designed to support solving combinatorial optimization problems using evolutionary algorithms. One of the main features of the system is tracking complex dependencies between parameters of an implemented algorithm with use of visualization. The role of the system is shown by its application to solve two problems: multiprocessor scheduling problem and Travelling Salesman Problem (TSP).

Finite-state automata are state-of-the-art representation of dictionaries in natural language processing. We present a novel compression technique that is especially useful for gazetteers – a particular sort of dictionaries. We replace common substructures in the automaton by unique copies. To find them, we treat a transition vector as a string, and we apply a Ziv-Lempel-style text compression technique that uses suffix tree to find repetitions in lineaqr time. Empirical evaluation on real-world data reveals space savings of up to 18,6%, which makes this method highly attractive.

Progress of automatic speech recognition systems’ (ASR) development is, inter alia, made by using signal representation sensitive for more and more sophisticated features. This paper is an overview of our investigation of the new context-sensitive speech signal’s representation, based on wavelet-Fourier transform (WFT), and proposal of it’s quality measures. The paper is divided into 5 sections, introducing as follows: phonetic-acoustic contextuality in speech, basics of WFT, WFT speech signal feature space, feature space quality measures and finally conclusion of our achievements.