In machine learning, the learner is assumed to be rational, seeking the highest probability, lowest cost, account of the data. This may not be achievable without a tremendous amount of data. Meanwhile, the problem of overfitting remains a formidable challenge: the best hypothesis from one set of data may not generalize well to another. Herbert Simon observed that human learning and decision-making often do not strive for optimal solutions but merely solutions that are good enough ("satisficin...