Stimulus Sampling Theory

Some of the fundamental mathematical techniques of stimuls sampling theory are presented and the oneelement model is worthy of study not only for expositional purposes but also for its value as an analytic device in relation to certain types of learning data.

Abstract

Abstract : Some of the fundamental mathematical techniques of stimuls sampling theory are presented. The simplest of all learning models - the pattern model for simple learning is presented in which the population of available stimulation is ASSUMED TO COMPRISE A SET OF DISTINCT STIMULUS PATTERNS, EXACTLY ONE OF WHICH IS SAMPLED ON EACH TRIAL. In the important special case of the oneelement model, it is assumed that there is only one such pattern and that it recurs intact at the beginning of each experimenta trial. The oneelement model is worthy of study not only for expositional purposes but also for its value as an analytic device in relation to certain types of learning data. After a treatment of pattern models for simple acquisition an for learning under probabilistic reinforcement schedules, the conceptualization of generalization and transfer is discussed; the component models in which the patterns of stimulation effective on individual trials are treated, not as distinct elements, but as overlapping samples from a common population; and, finally, some examples of the more complex multiple-process models which are becoming increasingly important in the analysis of discrimination learning, concept formation, and related phenomena are discussed. (Author)