id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_x23fdj3d5nafzcduwyfrwf6bna	Cailin O'Connor	Evolving to Generalize: Trading Precision for Speed	2015	23	.pdf	application/pdf	9882	817	61	evolutionary game theoretic models, however, learning generalization does present evolutionary game theoretic models of learning generalization and I present simulation results showing that despite the long-term success of nongeneralized learning, under certain parameter settings higher levels of that in evolutionary game theoretic models where short-term learning is important, learning generalization can evolve. These results indicate that the intuitive argument is right, and that ignoring short term behaviour of learning rules can lead evolutionary analyses significantly astray. Furthermore, as I shall show later in the article, considering games with large state spaces is relevant for understanding why generalized learning might evolve. A model of an approximation game evolved using these learning rules will What happens to the strategy of an actor using a GRL rule in the approximation game in the long run? Consider a model where a population of actors learns to play an approximation game using either Herrnstein learning or various GRL rules.	./cache/work_x23fdj3d5nafzcduwyfrwf6bna.pdf	./txt/work_x23fdj3d5nafzcduwyfrwf6bna.txt