Successive adaptation of neural networks in a multi-agent model

Abstract

This paper examines the adaptability of neural networks to gradual and sudden changes in the environment of a non-cooperative repeated market selection game. Neural networks are used as decision-making systems of agents for iterative game playing. Training data are successively generated from each round of our game by the neural networks.