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Although individual ants have an extremely basic intelligence, and are completely incapable of surviving on their own, colonies of ants can develop remarkably sophisticated and biologically successful behavior. This paper discusses a set of experiments which attempt to simulate one of these behaviors, namely the ability of ants to place pheromones as a way of communication. These experiments involved a variety of different environments, and tested two varieties of the genetic algorithm NEAT: the standard offline version, and its online counterpart rtNEAT. Since the experimental environment did not seem to offer any benefit to continuous learning, we had expected NEAT and rtNEAT to have roughly similar learning curves. However, our results directly contradict this hypothesis, showing much more succesful learning with rtNEAT than with standard NEAT.

Riget Workshop example 1. Minimal document showing off text formatting

Euclid's algorithm written out using the algorithmic environment in LaTeX.

International Mathematics Research Notices provides very fast publication of research articles of high current interest in all areas of mathematics. All articles are fully refereed and are judged by their contribution to advancing the state of the science of mathematics. For more information about the journal, see http://imrn.oxfordjournals.org/.

Plantilla de apoyo para la redacción del proyecto de título de la Universidad del Bío-Bío, con enfoque a la carrera de Ingeniería Civil Industrial (aunque sirve para otras)

Experimentalphysik 5: Kern- und Teilchenphysik

Jyothi Kunaparaju's résumé

Summary in LaTex for Great Math Mystery

Hudson School Lab Report Template