Evolving compression preprocessors with genetic programming
Johan Parent, Ann Nowé · 2002
We present a new approach for applying ge-netic programming to lossless data compres-sion. Unlike programmatic compression the evolved programs are preprocessors. These preprocessors aim at enhancing the compres-sion rate of the given data by transform-ing it. The entropy based tness function is both fast and independent of the type of information being processed. The obtained results are encouraging in sense that signi-cant improvements can be achieved. Further-more the required computation time is much smaller than in the case of programmatic compression, making the presented approach more viable. We used a strongly typed GP kernel. The kernel oers the extra advan-tage of being able to exploit parallel execu-tion through the island model. 1