Optimization Problem Solving using Predator/Prey Games and Cultural Algorithms

This paper looks at optimization problem solving from the standpoint of a predator/prey paradigm. In that paradigm, knowledge sources (or decision makers) control the placement of individuals onto a multi-dimensional landscape. Their score is the sum of the resources collected by each of the individuals that they control. While simple, this game has many of the properties present in much more complex real-time strategy games such as Age of Empires. In the next time step individuals are allocated from a fixed population to knowledge sources (empires) in proportion to the relative scores of the knowledge sources. This game is embedded in a cultural algorithm framework and we show how it can be used as a paradigm with which to study the optimization of an engineering design problem from a more strategic perspective