Evolving Cellular Automata to Perform User-Defined Computations

Abstract

A novel genetic algorithm for evolving both uniform and nonuniform cellular automata (CA) to perform user-defined computations is presented. Unlike previous approaches, the CAs evolved here can in general take as their input and their output only a subset of the cells, allowing for the design of CAs that are larger than the number of inputs required by the desired computation. It also provides greater flexibility compared with previous work in terms of the number of possible outputs. We test our algorithm by attempting to evolve both uniform and nonuniform 1D CAs of varying sizes to compute the sum of two 4-bit strings, a computation requiring 8 inputs and 5 outputs. Results demonstrate that while the algorithm is unable to discover solutions using 8-cell CAs, expanding the number of cells beyond the number of inputs enables the autonomous design of 4-bit adders.