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This work presents a cognitive and deterministic theory of learning and a related theory of performance. The authors assume that the organism is a logical system whose behavior is governed by its anticipation of the future, that this anticipation, called the expectancy, is the basic learning event, that the expectancy arises within a quasi-linguistic representational system, that the organism’s confidence in the expectancy changes during learning, and that the strength of the expectancy in real organisms is subjective probability. Carnap’s lambda-system of inductive logic is used as an approximation of subjective probability. Formulas from this framework are applied to conditioning, partial reinforcement, and other experimental data.
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This work presents a cognitive and deterministic theory of learning and a related theory of performance. The authors assume that the organism is a logical system whose behavior is governed by its anticipation of the future, that this anticipation, called the expectancy, is the basic learning event, that the expectancy arises within a quasi-linguistic representational system, that the organism’s confidence in the expectancy changes during learning, and that the strength of the expectancy in real organisms is subjective probability. Carnap’s lambda-system of inductive logic is used as an approximation of subjective probability. Formulas from this framework are applied to conditioning, partial reinforcement, and other experimental data.