Technological Innovation of High-Tech Industry ad Patent Policy: Agent Based simulation with Double Loop Learning

In this paper, we formulate a multi-agent model of virtual high-tech industry by agent-based simulation. We introduce a classifier system as a decision-making tool of agent who makes its decision depending on the rules in the classifier system. Firm agent determines how much RD also agents may change their goals (evaluation functions) when they have survival problem in industry. We verify the Schumpeter Hypothesis and effect of industrial policies in our virtual high-tech industry. We found that the difference in speed at which technology increases, when comparing imitation and innovation, affects the effectiveness of patent policy.