Stochastic Models for Learning
Robert R. Bush,Frederick Mosteller
Stochastic Models for Learning
Robert R. Bush,Frederick Mosteller
2012 Reprint of 1955 Edition. Exact facsimile of the original edition, not reproduced with Optical Recognition Software. A stochastic process is one in which the probabilities of a set of events keep changing with time. Bush and Mosteller make use of the mathematical techniques developed for the study of such processes in building a theory of learning and then apply the theory to explain the results of several learning experiments. Contents: Part I: The mathematical system and the general model – 1. The basic model – 2. Stimulus sampling and conditioning – 3. Sequences of events – 4. Distributions of response probabilities – 5. The equal alpha condition – 6. Approximate methods – 7. Operators with limits zero and unity – 8. Commuting operators – Part II: Applications – 9. Identification and estimation – 10. Free-recall verbal learning – 11. Avoidance training – 12. An experiment on imitation – 13. Symmetric choice problems – 14. Runway experiments – 15. Evaluations.
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