on the deleterious effects of a priori objectives on evolution and representation
Evolutionary algorithms are often evaluated by measuring and comparing their ability to consistently reach objectives chosen a priori by researchers. Yet recent results from experiments without explicit a priori objectives, such as in Picbreeder and with the novelty search algorithm, raise the question of whether the very act of setting an objective is exacting a subtle price. Nature provides another hint that the reigning objective-based paradigm may be obfuscating evolutionary computation's true potential; after all, many of the greatest discoveries of natural evolution, such as flight and human-level intelligence, were not set as a priori objectives at the beginning of the search. The dangerous question is whether such triumphs only result because they were not objectives. To examine this question, this paper takes the unusual experimental approach of attempting to re-evolve images that were already once evolved on Picbreeder. In effect, images that were originally discovered serendipitously become a priori objectives for a new experiment with the same algorithm. Therefore, the resulting failure to reproduce the very same results cannot be blamed on the evolutionary algorithm, setting the stage for a contemplation of the price we pay for evaluating our algorithms only for their ability to achieve preconceived objectives.
representations deception non-objective search stepping stones fitness indirect encoding