A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.

Particle swarm optimization

Conservationists are far from able to assist all species under threat, if only for lack of funding. This places a premium on priorities: how can we support the most species at the least cost? One way is to identify 'biodiversity hotspots' where exceptional concentrations of endemic species are undergoing exceptional loss of habitat. As many as 44% of all species of vascular plants and 35% of all species in four vertebrate groups are confined to 25 hotspots comprising only 1.4% of the land surface of the Earth. This opens the way for a 'silver bullet' strategy on the part of conservation planners, focusing on these hotspots in proportion to their share of the world's species at risk.

Biodiversity hotspots for conservation priorities

A concept for the optimization of nonlinear functions using particle swarm methodology is introduced The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed The relationships between particle swarm optimization and both artificial life and genetic algorithms are described

/pdf/particle-swarm-optimization-r1hjpa7ad3.pdf

Cooperation in organisms, whether bacteria or primates, has been a difficulty for evolutionary theory since Darwin. On the assumption that interactions between pairs of individuals occur on a probabilistic basis, a model is developed based on the concept of an evolutionarily stable strategy in the context of the Prisoner's Dilemma game. Deductions from the model, and the results of a computer tournament show how cooperation based on reciprocity can get started in an asocial world, can thrive while interacting with a wide range of other strategies, and can resist invasion once fully established. Potential applications include specific aspects of territoriality, mating, and disease.

/pdf/the-evolution-of-cooperation-pwc4krac7e.pdf

The Evolution of Cooperation

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Collecting, Culturing, Observing

Teoría de la biogeografía insular

Animal behavior: Readings from Scientific American

인간 본성에 대하여

Nomenclatural procedures in animal taxonomy, especially the application of priority rules in the vast entomological literature, are oppressively inefficient and becoming more so with the passage of time. The authors suggest that the problem be solved in a simple but radical way, by the device of officially recognizing selected monographs as the "new Linnaeus" of the group treated by the monograph. No publication prior to the monograph could then affect nomenclatural usage in the group, but a new monograph could supplant it.

https://www.jstor.org/stable/info/2412362

Edward O. Wilson

Papers

Collecting, Culturing, Observing

Teoría de la biogeografía insular

Animal behavior: Readings from Scientific American

인간 본성에 대하여

A suggested revision of nomenclatural procedure in animal taxonomy