Organizational Knowledge, Cognitively Plausible Actors and Multi-Actor Systems

Abstract

Organizational knowledge and knowledge management can only be studied successfully if two basic requirements are fulfilled: (1) determination of what knowledge is about and which carriers of knowledge are allowed and (2) the mechanisms that provide the interaction between the carriers (actors and software agents). We therefore have to step down to a lower level of aggregation, that is to say, to actors, to (shared) mental models, to agents and to the interaction between them. In order to guide the study of these constituting elements we formulate two questions. (A) What is the difference between information and knowledge and what consequences does this difference have for corporate and organizational issues? (B) If the human individual is one kind of actor, what other kind of actors (or agents) can we discern, what characteristics do the various actors have and what mechanisms are used to collaborate in Multi-Actor Systems (MAS)? Insights from cognitive science, artificial intelligence and knowledge technology are used to answer the questions. We see knowledge as interpreted information. For the time being only human actors can entertain knowledge, because they have representations. Taking into account other components of (intelligent) actors, such as perception and interaction, other kinds of actors (and agents) can be defined. Various kinds of actors (and agents) may work together in an organization, which we call a Multi-Actor System. The "glue" that keeps such a system together is called: coordination mechanism. Various kinds of coordination mechanisms exist such as standardization, authority, and mutual adjustment. This also depends on the characteristics of the involved actors. The perspective of cognitive science combined with the assumption that organizations are a MAS make "organizational knowledge" and "organization" operational, measurable and quantifiable. Especially the focus on actor characteristics and as a result the actor/agent taxonomy being combined in a multi-actor system with various coordination mechanisms, makes it a better framework for an easy and smooth inclusion of and integration with (software) agents. NR - 45 PU - SPRINGER PI - NEW YORK PA - 233 SPRING STREET, NEW YORK, NY 10013, UNITED STATES