Time in Genetic Algorithms

Time in Genetic Algorithms

Abstract:

One of the most intriguing aspects of genetic algorithms is that of time. However, the temporal aspect is mostly treated from a dynamic perspective, based on Markov chains or similar process paradigms.

This paper tries to describe the genetic algorithm from a novel viewpoint: that of a temporal logic combined with probabilistic constructs in a unified way enabling us to ask important questions, e.g. what are the conditions for convergence or how can I describe the converged population from a global perspective.

Keywords: temporal logic , probabilistic logic 

• Introduction
• Temporal Probabilistic Logic
  • Temporal Logic
  • Probabilistic Logic
• Genetic algorithm objects
• Population characteristics
• Convergence and optima
• Conclusions
• Bibliography