Complex Evolution and Learning

Abstract

Searching and learning are key processes in determining the complex evolution of technological capabilities but take place according to idiosyncratic rules that constrain the way they unfold. In this respect, constraints are often understood as barriers hampering efficient functioning. They are, indeed, seen as orienting activity in specified directions generating performance patterns the upshot of which is likely to be suboptimal. This view may be thought as applying to the domain of social undertakings as well as to activities of a biological nature. Constraints are thus perceived as fetters to efficiency, bounding the required freedom often deemed as crucial to achieve, if not optimal, at least improving solutions. In a recent paper (Ricottilli 2008), it has been argued that constraints set to restrain full freedom of choice, but the argument may well apply to across-the-board functioning of biological entities, act as focusing devises quite often resulting in better performance. The problem at hand takes full contours when dealing with the issue of searching and learning, that is when problem-solving is set in an evolutionary, hence dynamic, context. More particularly, this issue is of utmost relevance when this process is meant to lead to innovation, be it technological or organizational or, in fact, both. It is a well established fact that a firm's strategy to survive and thrive in a market environment does require innovative activity and investment. Although markets rarely function according to the classical competitive paradigm, they become contestable precisely thanks to the likelihood of product and process innovation. It is therefore important that a model of searching and learning take fully into account the role that constraints are likely to play in these processes.