| Optimal Properties of Stimulus-Response Learning Models (1998) | |||||||||||||||||
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| We consider stimulus-response models of learning: an agent chooses an action with a probability, which is increasing in the payoff that has been associated to that action in past periods. A procedure is a specific way of making this association. We say that a procedure is optimal if the sequence of choices it generates converges to the action that maximizes the expected payoff. Which procedures are optimal depends in a substantial way on the information available to the agent. We say that an individual learning in isolation has partial information, because he can only observe the payoff to the action he has chosen; in social learning, he has full information, because he can learn from the action of the others the payoff associated to each action. The main conclusion of the paper is that linear procedures always converge to optimal action in the case of partial information, and do not in the case of full information. Exactly the opposite is true in the case of exponential procedures:... | |||||||||||||||||
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