Gessler, Nicholas. “Evolving Artificial Cultural Things-That-Think and Work by Dynamical Hierarchical Synthesis.” Association for the Advancement of Artificial Intelligence Proceedings (2003).
URL1 URL2
Growth in the new sciences of complexity relies on the intermediation of two lines of research. On the one hand, we must develop an effective means of representing both complexity and its entailments. On the other, we must examine the empirical world with freshly calibrated eyes. The two are intimately intertwined, for without an adequate language of description and synthesis complexity will always lay just outside our ken and understanding, and without direct confirmation from the real world complexity will always an esoteric speculation The psychology of perception is such that without a formal way of representing and talking about complexity one is likely to not recognize it at all and so settle for some gross abstraction of events. In the empirical world disorder is casually dismissed as noise. We do not see what we are not looking for. Innovation in science thus requires new ways of looking at the world, new ways of looking at old theories and data. Recognizing complexityrequires new ways of knowing. Discovery is seeing what has not previously been seen.