BOTTOM‐UP AND DEVELOPMENTAL APPROACHES
BOTTOM‐UP AND DEVELOPMENTAL APPROACHES
This chapter surveys bottom‐up approaches to the development of artificial moral agents. These approaches apply methods from machine learning, Kohlberg's theory of moral development, and techniques from artificial life (Alife) and evolutionary robotics, such as evolution through genetic algorithms, to the goal of facilitating the emergence of moral capacities from general aspects of intelligence. Such approaches hold out the prospect that moral behavior is a self‐organizing phenomenon in which cooperation and a shared set of moral instincts (if not a “moral grammar”) might emerge – this despite the logic of game theory which seems to suggest only self‐interested rationality can prevail in an evolutionary contest. A primary challenge for bottom‐up approaches is how to provide sufficient safeguards against learning or evolving bad behaviors as well as good.
Keywords: artificial life, cooperation, emergence, evolution, game theory, genetic algorithm, Kohlberg, moral development, moral grammar, evolutionary robotics
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