Neural-Evolutionary Learning in a Bounded Rationality Scenario

Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of a population of neural networks in order to make a decision, while inductive learning is performed by means of an evolutionary algorithm. We show that good convergence to the game-theoretic equilibrium is reached within certain parameters.

• Type: Conference
• Year: 2004
• Where: ICONIP
• Authors: Ricardo Matsumura de Araújo, Luís C. Lamb
• Keywords: Game-theoretic Equilibrium, ICONIP 2004, ICONIP 2007, Neural-evolutionary Framework, Rationality Scenario