Simulating knowledge dynamics in innovation networks (SKIN)

An agent-based simulation model representing a theory of the dynamic processes involved in innovation in modern knowledge-based industries is described. The agent-based approach allows the representation of heterogeneous agents that have individual and varying stocks of knowledge. The simulation is able to model uncertainty, historical change, effect of failure on the agent population, and agent learning from experience, from individual research and from partners and collaborators. The interactions between the agents occur on two levels: through a market with firms supplying and consuming goods for a price, and through the exchange of knowledge. A brief description of the implementation of the model and its user interface is given.