The application of software visualization technology to evolutionary computation: a case study in Genetic Algorithms

Evolutionary computation is an area within the field of artificial intelligence that is founded upon the principles of biological evolution. Evolution can be defined as the process of gradual development. Evolutionary algorithms are typically applied as a generic problem solving method, searching a problem space in order to locate good solutions. These solutions are found through an iterative evolutionary search that progresses by means of gradual developments. In the majority of cases of evolutionary computation the user is not aware of their algorithm's search behaviour. This causes two problems. First, the user has no way of assuring the quality of any solutions found other than to compare the solutions found by the algorithm with any available benchmark solutions or to re-run the algorithm and check if the results can be repeated or improved upon. Second, because the user is unaware of the algorithm's behaviour they have no way of identifying the contribution of the different components of the algorithm and therefore, no direct way of analyzing the algorithm's design and assigning credit to good algorithm components, or locating and improving ineffective algorithm components. The artificial intelligence and engineering communities have been slow to accept evolutionary computation as a robust problem-solving method because, unlike cased-based systems, rule-based systems or belief networks, they are unable to follow the algorithm's reasoning when locating a set of solutions in the problem space. During an evolutionary algorithm's execution the user may be able to see the results of the search but the search process itself like is a "black box" to the user. It is the search behaviour of evolutionary algorithms that needs to be understood by the user, in order for evolutionary computation to become more accepted within these communities. The aim of software visualization is to help people understand and use computer software. Software visualization technology has been applied successfully to illustrate a variety of heuristic search algorithms, programming languages and data structures. This thesis adopts software visualization as an approach for illustrating the search behaviour of evolutionary algorithms. Genetic Algorithms ("GAs") are used here as a specific case study to illustrate how software visualization may be applied to evolutionary computation. A set of visualization requirements are derived from the findings of a GA user study. A number of search space visualization techniques are examined for illustrating the search behaviour of a GA. "Henson," an extendable framework for developing visualization tools for genetic algorithms is presented. Finally, the application of the Henson framework is illustrated by the development of "Gonzo," a visualization tool designed to enable GA users to explore their algorithm's search behaviour. The contributions made in this thesis extend into the areas of software visualization, evolutionary computation and the psychology of programming. The GA user study presented here is the first and only known study of the working practices of GA users. The search space visualization techniques proposed here have never been applied in this domain before, and the resulting interactive visualizations provide the GA user with a previously unavailable insight into their algorithm's operation

The personality systems framework: Current theory and development

The personality systems framework is a fieldwide outline for organizing the contemporary science of personality. I examine the theoretical impact of systems thinking on the discipline and, drawing on ideas from general systems theory, argue that personality psychologists understand individuals’ personalities by studying four topics: (a) personality’s definition, (b) personality’s parts (e.g., traits, schemas, etc.), (c) its organization and (d) development. This framework draws on theories from the field to create a global view of personality including its position and major areas of function. The global view gives rise to new theories such as personal intelligence—the idea that people guide themselves with a broad intelligence they use to reason about personalities

Regulating Evolution for Sale: An Evolutionary Biology Model for Regulating the Unnatural Selection of Genetically Modified Organisms

In recent years, there has been an explosion in the genetic manipulation of living organisms to create commercial products. This genetic manipulation has, in effect, been a directed change in the evolutionary process for the purpose of profit. This deliberate alteration of the path of evolution has brought with it a panoply of novel environmental, human health, and economic risks that could not have been foreseen when U.S. environmental and health protection laws evolved. U.S. environmental law has not evolved to keep pace with these dramatic changes in the evolution of our biological systems. Thus, completely new approaches are needed to address these novel issues. The thesis of this Article is that a new legal approach, which draws on principles of evolutionary biology, is needed to address the novel risks of environmental harm caused by man\u27s intervention in and manipulation of evolution through the development of GMOs

Framing purposeful evaluation through critical systems thinking

Two traditions of practice – evaluation and systems – share three significant concerns regarding development intervention: (i) making sense of complex interrelationships and the continual change brought about by such relationships; (ii) engaging with multiple (including exogenous and endogenous), often conflicting, perspectives on situations; and (iii) challenging vicious cycles of practice and understanding by cultivating a more radical learning culture. These challenges might be described successively in terms of cultivating a shift from (i) summative to formative evaluation (ii) positional bargaining to interest based negotiation, and (iii) purposive to purposeful action. Some ideas from traditions of social learning and critical systems thinking are presented to support a re-framing of intervention and evaluation from one serving the 'project state' towards one serving more radical transformative practice

Regulating Evolution for Sale: An Evolutionary Biology Model for Regulating the Unnatural Selection of Genetically Modified Organisms

In recent years, there has been an explosion in the genetic manipulation of living organisms to create commercial products. This genetic manipulation has, in effect, been a directed change in the evolutionary process for the purpose of profit. This deliberate alteration of the path of evolution has brought with it a panoply of novel environmental, human health, and economic risks that could not have been foreseen when U.S. environmental and health protection laws evolved. U.S. environmental law has not evolved to keep pace with these dramatic changes in the evolution of our biological systems. Thus, completely new approaches are needed to address these novel issues. The thesis of this Article is that a new legal approach, which draws on principles of evolutionary biology, is needed to address the novel risks of environmental harm caused by man\u27s intervention in and manipulation of evolution through the development of GMOs

GAMETH A Process Modeling Approach to Identify and Locate Crucial Knowledge.

In a knowledge management initiative, one of the main issues is to identify and locate which knowledge to capitalize on. To deal with this issue, a General Analysis Methodology so called GAMETH® has been developed. In this article, we describe the postulates, the guiding principles, and the main phases, which constitute the basis of GAMETH® Framework. Notably, we emphasize the process modeling approach that is inherent to the second phase of the methodology. This process modeling approach supports the effective capability to locate and identify “crucial knowledge”. Furthermore, we present lessons learned from two case studies.Process modeling; Knowledge Management (KM); GAMETH; Identifying and Locating Company’s Crucial Knowledge; Crucial knowledge;

SOA and BPM, a Partnership for Successful Organizations

In order to stay effective and competitive, companies have to be able to adapt themselves to permanent market requirements, to improve constantly their business process, to act as flexible and proactive economic agents. To achieve these goals, the IT systems within the organization have to be standardized and integrated, in order to provide fast and reliable data access to users both inside and outside the company. A proper system architecture for integrating company’s IT assets is a service oriented one. A service-oriented architecture (SOA) is an IT architectural style that allows integration of the company’s business as linked, repeatable tasks called services. A subject closely related to SOA is Business Process Management (BPM), an approach that aims to improve business processes. The paper also presents some aspects of this topic, as well as the relationship between SOA and BPM. They complement each other and help companies improve their business performance.Information Systems, SOA, Web Services, BPM

Regulating Evolution for Sale: An Evolutionary Biology Model for Regulating the Unnatural Selection of Genetically Modified Organisms

In the past ten years there has been an explosion in the genetic manipulation of living organisms to create commercial products. This genetic manipulation has, in effect, been a directed change in the evolutionary process for the purpose of profit. This deliberate alteration of the path of evolution has brought with it a panoply of novel environmental, human health, and economic risks that could not have been foreseen when U.S. environmental and health protection laws evolved. Many products of genetic engineering have been modified to possess traits that increase their ability to reproduce and survive in the environment. By genetically manipulating microorganisms, plants, and animals to make them more “fit” from an evolutionary standpoint, science has altered the path of evolution to favor not those organisms that have evolved to be more fit for their natural environment, but instead those organisms that have become more fit at the hand of humans for commercialization and profit-making. U.S. environmental law has not evolved to keep pace with these dramatic changes in the evolution of biological systems and has been constrained by outdated policies adopted in the 1980s. Accordingly, the law governing GMOs has emerged as a piecemeal patchwork of regulations implemented by three federal agencies plagued by interagency turf battles, bureaucratic inertia, and conflicting regulatory standards. The thesis of this Article is that a new legal approach, which draws on principles of evolutionary biology, is needed to address the novel risks of environmental harms caused by man’s intervention in, and manipulation of, evolution through the development of GMOs. This Article is the first to analyze the complete array of U.S. regulatory programs addressing GMOs and the adequacy of these programs to address the novel elements of risk posed by GMOs. Moreover, this Article is the first ever to propose a new approach to regulation of GMOs utilizing principles drawn from evolutionary biology theory. By applying evolutionary biology theory to the regulation of GMOs, this Article provides a comprehensive legal framework for determining which GMOs should be permitted to be released into the environment under what conditions. This approach has the potential to revolutionize environmental law as it relates to GMOs, as well as to other artificially cultivated living organisms