The current concept of information has two major deficiencies: it is static, and it does not respect the properties of human information processing. In this book the authors suggest that generation of events can be related to interpretation, and probabilistic analysis of events can be related  to learning. They concentrate on the introduction of a theory of interpretation. They define a model that enables a meaningful representation of information, based on a dynamic view of information and a cognitive model of human information processing.  The book consists of three parts. The first part focuses on the properties of signs and sign interpretation; in the second part the authors introduce a model that complies with the conditions for sign processing set by the first part; and in the third part they examine various applications of their model. They concentrate throughout on the presentation of a theory of knowledge representation and we will illustrate this theory with a number of examples The reader is assumed to have some interest in human information processing and knowledge modeling in domains such as natural language, logic, mathematics and reasoning. Natural language is considered in the obvious sense, familiarity with linguistic theories is not required. Sign theoretical concepts are restricted to a manageable subset, which is introduced gently. Some familiarity with basic concepts of propositional and syllogistic logic may be useful.