CONTINGENCY AND ITS 2 INDEXES WITHIN CONDITIONAL-PROBABILITY ANALYSIS

Four theoretical bases for detecting a contingency between behavior an d consequent stimuli are considered: contiguity, correlation, conditio nal probability, and logical implication. It is argued that conditiona l probability analysis is statistically the most powerful of these opt ions, in part due to its provision of two indices of contingency: a fo rward time probability that reinforcement follows behavior and a backw ard time probability that behavior precedes reinforcement. Evidence is cited that both indices appear to bear on the learning of a variety o f animals, although they are unequally salient to human adults and to artificial neural networks designed to solve time-series functions. It is hypothesized that humans may acquire the capacity to detect contin gency in the progressive sequence: contiguity, correlation, forward ti me conditional probability, backward time conditional probability, and ultimately logical implication.