Hampshire College

About: Hampshire College is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Genetic programming & Population. The organization has 461 authors who have published 998 publications receiving 40827 citations.

Use of entanglement in quantum optics

Abstract: Several recent demonstrations of two-particle interferometry are reviewed and shown to be examples of either color entanglement or beam entanglement. A device, called a number filter, is described and shown to be of value in preparing beam entanglements. Finally, we note that all three concepts (color and beam entaglement, and number filtering) may be extended to three or more particles.

An Inclusive Perspective

Abstract: Mathematics Elsewhere . An Exploration of Ideas Across Cultures. Marcia Ascher. Princeton University Press, Princeton, NJ, 2002. 219 pp. $24.95, £17.95. ISBN 0-691-07020-2. In this follow-up to her earlier Ethnomathematics , Ascher discusses the treatment of topics such as views of time, the future, maps, and mathematical relations in a variety of traditional and small-scale cultures.

Class structure and rural self-help in Kenya and Tanzania

Abstract: Comparisons of development in neighbouring Kenya and Tanzania are a ""natural"" enterprise although there have been few explicit attempts to date.

Fecundity and selectivity in evolutionary computation

Abstract: The number of offspring produced by each parent---that is, the fecundity of reproducing individuals---varies among evolutionary computation methods and settings. In most prior work fecundity has been tied directly to selectivity, with higher selection pressure giving rise to higher fecundity among individuals selected to reproduce. In nature, however, there is a wider variety of strategies, with different organisms producing different numbers of offspring under the influence of a range of factors including not only selection pressure but also other factors such as environmental stability and competition within a niche. In this work we consider possible lessons that may be drawn from nature's approaches to these issues and applied to evolutionary computation systems. In particular, we consider ways in which fecundity can be dissociated from selectivity and situations in which it may be beneficial to do so. We present a simple modification to the standard evolutionary algorithm, called decimation, that permits high fecundity in conjunction with modest selection pressure and which could be used in various forms of evolutionary computation. We also present a simple example, showing that decimation can improve the problem-solving performance of a genetic algorithm when applied to a deceptive problem.