Cellz: a simple dynamic game for testing evolutionary algorithms

Abstract

The game of Cellz has been designed as a test bed for evolutionary algorithms. The game has a minimal set of rules that nonetheless offer the possibility for complex behaviour to emerge. Computationally, the game is cheap to simulate, which leads to rapid runs of evolutionary algorithms. A key feature of the game is the cell division process, which can lead to evolution in situ without reference to any externally defined fitness function. This paper describes the rationale behind the development of Cellz, the rules of the game and the software interfaces for the cell controllers. The randomness in the game initialisation leads to extremely noisy fitness functions, which adds to the challenge of evolving high-performance controllers. Initial results demonstrate that an evolved perceptron-type controller can achieve mediocre performance on the single species game.