1. Stimulus Sampling Theory

2. Agenda Stimulus Sampling Theory overview Analytic & simulation models Estes & Straughan, 1954 Homeworks 1 & 2

3. Stimulus Sampling Theory Stimulus Elements  is Stimulus S 1  is Associated With A  is Associated With B  is Activated on Trial n  is = Prob of sampling Element i given Stimulus S

4. Stimulus Sampling Theory Stimulus Elements  is Stimulus S 1 P(A) = 1/4

5. Stimulus Sampling Theory Stimulus Elements  is Stimulus S 1 Feedback for A

6. Stimulus Sampling Theory Stimulus Elements  is Stimulus S 2

7. Stimulus Sampling Theory Stimulus Elements  is Stimulus S 2 P(A) = 1/2

8. Stimulus Sampling Theory Stimulus Elements  is Stimulus S 2 Feedback for B

9. An Example One of two stimuli, Red A or Blue B, appear. You are simply to learn when to press a button.

10. An Example A.1.3 P(Press) = 0/3

11. An Example A.1.3 Feedback = Press

12. An Example B.3.1.2.3.1.3 P(Press) = 1/2

13. An Example B.3.1.2.3.1.3 Feedback = No Press

14. An Example B.3.1.2.3.1.3 P(Press) = 0/2

15. An Example B.3.1.2.3.1.3 Feedback = Press

16. A Modern Example 251723952378 PhonologyOrthographySemanticsContext

17. What are Stimulus Elements? “The concept of stimulus element is not defined in terms of observable events; it has the status of a primitive term within the theory” (p. 4). “Relating experimental manipulations to a stimulus sampling parameter … is by no means necessary … for the derivation of testable predictions. To the extent that directly testable implications of the theory are supported by evidence, the concepts of stimulus sampling remain tenable” (p. 4).

18. Is Stimulus Sampling Theory a Model? “The term ‘stimulus sampling theory’ refers to a number of theories differing with respect to special assumptions and their mathematical expression, yet sharing a common approach to conceptual representation of the stimulus situation and the formation of associative connections, rather than to a single coherent set of assumptions formulated to apply to all the experimental procedures employed in the study of learning” (p. 1).

19. Analytic & Simulation Models An analytic solution to a model is one in which an equation is used to describe the output of the model. A simulation result is produced by following a set of procedures.

20. Analytic & Simulation Models 1)Sample S’ from S on Trial n 2)P(A) = Proportion A from S’ 3)Associate S’ with feedback 4)Go to 1

21. Analytic & Simulation Models In general, an analytic solution is preferred. –Less prone to specific sequences. –Can often make the same predictions as simulation. –Faster. Especially in fitting programs. –Easier.