Simulation for the Social Scientist
Simulation for the Social Scientist
Innovation Networks: Theory and Practice
Innovation Networks: Theory and Practice
Handbook of Research on Nature-inspired Computing for Economics and Management
Handbook of Research on Nature-inspired Computing for Economics and Management
Guest editorial agent-based modeling of evolutionary economic systems
IEEE Transactions on Evolutionary Computation
A NEO-SCHUMPETERIAN MODEL OF ENERGY MARKETS
Cybernetics and Systems - BEST OF AGENT-BASED MODELING AND SIMULATION 2008
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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 heterogenous 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 aim of the simulation exercises is to show that the artificial innovation networks show certain characteristics they share with innovation networks in knowledge intensive industries and which are difficult to be integrated in traditional models of industrial economics.