Evolving Blackjack Strategies Using Cultural Learning

摘要

This paper presents a new approach to the evolution of blackjack strategies, that of cultural learning. Populations of neural network agents are evolved using a genetic algorithm and at each generation the best performing agents are selected as teachers. Cultural learning is implemented through a hidden layer in each teacher's neural network that is used to produce utterances which are imitated by its pupils during many games of blackjack. Results show that the cultural learning approach outperforms previous work and equals the best known non-card counting human approaches.