View article

This study describes a novel simulation model of the process of product invention (InventSim). Invention is conceptualized as search on a landscape of product design possibilities, by a population of profit-seeking agents (inventors). The search process embeds both social and individual learning and is modelled using a memetic-type algorithm. The algorithm includes the search heuristics of thought experiments and election. This study examines the impact of these heuristics on the rate of invention in a society where inventors' estimates of the expected fitness (payoffs) of proposed inventions are noisy. The simulation results indicate that the heuristics are crucial in driving forward the inventive process even when payoff expectations are noisy.