The anticipatory profile. An attempt to describe anticipation as process

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Inductive class representation and the more comprehensive evolving transformation system (ETS) are congenial to the subject matter of anticipation. In substantiating this assertion, we examine the epistemological premises of a new form of representation, of interest to pattern recognition and Artificial Intelligence (AI), but even more to the study of living systems. Some concepts, such as classes, time and time scale, and generative processes are examined in detail with respect to their pertinence to anticipation. Finally, pattern generation and ETS programming are suggested. Now when we get to the inductive stage what we are about is finding out how much like the truth our hypothesis is, that is, what proportion of its anticipations will be verified. 1. Introduction The question of whether real-life phenomena – ranging from those that fit deterministic descriptions to more complex developments – can be specified in some systematic manner becomes more critical as the state of available knowledge elicits more daring scientific concepts, such as those advanced in genetic medicine, nanotechnology, bioengineering, and quantum computation, to name just a few. The expectation of uniform expression of knowledge has never been higher, although the variety of forms through which knowledge is acquired and disseminated is increasing very fast. These epistemological themes are unavoidable, especially in pursuing research work at the confluence of several disciplines. As much as specialization has contributed to our understanding of the world, the major challenge in our days is no longer to explore the centre (of a particular discipline), but the vast area of shared interest among many specializations. Accordingly, scientists cannot escape asking questions formerly relegated to philosophers, and somehow understood as having only philosophical significance. 'How is knowledge represented across disciplines?' is such a question.