Evolutionary computation has started to receive significant attention during the last decade, although the origins can be traced back to the late 1950's. This article surveys the history as well as the current state of this rapidly growing field. We describe the purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA) (with links to genetic programming (GP) and classifier systems (CS)), evolution strategies (ES), and evolutionary programming (EP) by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism). Finally, we give a brief overview on the manifold of application domains, although this necessarily must remain incomplete.

/pdf/evolutionary-computation-comments-on-the-history-and-current-2wv5xjjqp7.pdf

Evolutionary computation: comments on the history and current state

IN RECENT years, economists have devoted a great deal of effort to developing and quantifying the concept of "human capital" and to applying it, through the concept of investment in the formation of human capital, to such activities as education, whether academic study or on-the-job training, migration, and medical care.' The concept of human capital, however, is by no means new. The object of this paper is to review some of the past literature, in order primarily to determine which authors treated human beings as capital, their motives for doing so, and their procedures for valuing man as capital. Although this essay is not exhaustive, it will be shown, in essence, that the concept of human capital was somewhat prominent in economic thinking until Marshall discarded the notion as "unrealistic." Economists who considered human beings or their skills as capital include such well-known names in the history of economic thought as Petty, Smith, Say,

https://www.jstor.org/stable/pdfplus/1829595.pdf

The Historical Roots of the Concept of Human Capital

After a short history of the concept of human capital (henceforth HC) in economic thought (Section 1), this study presents the two main methods for estimating the value of the stock of HC – the retrospective and prospective one – with a review of the models proposed (Section 2). These methods are linked both to the theory of HC investment as a rational choice (Section 3), the literature analysing the contribution of HC investment to economic growth and the HC estimating method through educational attainment (Section 4). The more recent literature on HC as a latent variable is also assessed (Section 5) and a new method of estimation where HC is seen both as an unknown function of formative indicators and as a ‘latent effect’ underlying earned income is proposed (Section 6). Section 7 concludes.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-6419.2009.00614.x

Human capital measurement: a survey

An artificial neural network with all its elements is a rather com- plex structure, not easily constructed and/or trained to perform a particular task. Consequently, several researchers used genetic algorithms to evolve partial aspects of neural networks, such as the weights, the thresholds, and the network architecture. Indeed, over the last decade many systems have been developed that perform total network induction. In this work it is shown how the chromosomes of Gene Expression Programming can be modified so that a complete neural network, including the architecture, the weights and thresholds, could be totally encoded in a linear chromosome. It is also shown how this chromosomal organization allows the train- ing/adaptation of the network using the evolutionary mechanisms of selec- tion and modification, thus providing an approach to the automatic design of neural networks. The workings and performance of this new algorithm are tested on the 6-multiplexer and on the classical exclusive-or problems.

/pdf/designing-neural-networks-using-gene-expression-programming-16l4f461r3.pdf

Designing Neural Networks Using Gene Expression Programming

http://www.genetic-programming.com/jkpdf/cmame.pdf

Synthesis of topology and sizing of analog electrical circuits by means of genetic programming

Proceedings of the First Annual Conference of the Wharton School of Finance and Commerce

The Human Value in Business Compared with the Property Value

The American College of Life Underwriters

Manager's Magazine

The Economics of Life Insurance

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