The paper is devoted to dynamic and context-dependent aspects of knowledge and reasoning. The main attention is focused on a relationship between belief revision and inference.

Abstract: It is often claimed that the symbolic approach to information processing is incompatible with connectionism and other associationist modes of representing information. I propose to throw new light on this debate by presenting two examples of how logic can be seen as emerging from an underlying information dynamics. The first example shows how intuitionistic logic results very naturally from an abstract analysis of the dynamics of information. The second example establishes that the activities of a large class of neural networks may be interpreted, on the symbolic level, as nonmonotonic inferences. On the basis of these examples I argue that symbolic and non-symbolic approaches to information can be described in terms of different perspectives on the same phenomenon. Thus, I find that Fodor and Pylyshyn’s claim that connectionist systems cannot be systematic and compositional is based on a misleading interpretation of representations in such systems.