Dynamic Models for Ideas Number Prediction in Brainstorming

In this paper, we extend the approach presented in [1] to the cognitive model of brainstorming proposed by Brown and Paulus in [4]. In their work Brown and Paulus developed two dynamic models of brainstorming, a non-cognitive model and a cognitive model. These models describe for each participant, the evolution of ideas number over time, and are formalized by differential equations. Through solution functions of these models, we propose to calculate the number of ideas of each participant on any time intervals and thus in the future (called prediction). To enable computing solution functions, we used an optimization model to determine the model parameter values. In this paper, we propose an optimization model based on the fourth order Runge-Kutta´s numerical method and we apply it to the cognitive model. Through some feasibility tests, we show the adequacy of the proposed approach to our prediction context.