Study objectives: The purpose of the present paper is to describe the concept of operant variability. Operant variability is difficult to explain because of its abstract nature. In order to elucidate this concept and distill the axes of previous studies, a preliminary discussion covered: (1) usage of the concepts of operant and variability in behavior analysis, and (2) an analysis of procedures that studies in this area often use. Next, published research examining the validity of variability as an operant was discussed in terms of the relation between differential reinforcement and behavioral variability. Conclusion: Operant behavior does not have a dimension of variability that can be a target of differential reinforcement, but it does have that dimension as an internal parameter of the behavior.

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Recent developments in research on behavioral variability have brought forth new technologies for controlling variable behavior with reinforcement schedules; these new technologies can also be applied to shaping procedures. Through the new technologies, it has been demonstrated that human sensitivity to schedules is closely related to variability in interresponse time. The present article discusses 2 issues related to these findings: (1)a problem in the causal relation between behavioral variability and schedule sensitivity, and (2)when variables have had some effect on human performance, the possibility that some variable such as instruction or reinforcement history has resulted in a change in the variability of the behavior, and that this, in turn, has directly changed the performance. The relationship between behavioral variability and schedule sensitivity indicates the importance of the viewpoint of variation and selection in human behavior. Recent examination of selection theory has expanded its subject to life phenomena broadly, not only biological evolution and operant conditioning, but also other phenomena such as the development of the immune system and neurons. Research on human behavioral variability will progress if it adopts the viewpoint of universal selection theory.

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The present review of operant variability describes some new implications of bridge studies for applied behavior analysis. A definition of operant variability is presented, and bridge studies of operant variability are identified and reviewed. The review suggests that the domains in bridge studies include developmental disabilities, psychopathology, and creativity. Implications of bridge studies for applied behavior analysis that are described include : (1) evoking more attention to various dimensions of target behavior, (2) increasing the sophistication of methodology and technology for behavioral structure, and (3) reflecting on implicit values involved in implementing research and providing service.

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The present article reviews experimental studies in the past 50 years on random number generation, and recent developments in behavioral variability research. The former approach, in an attempt to have people generate series of numbers as randomly as possible, has 3 problems: (1) the verbal instructions used, such as "be random," are ambiguous, (2) the participants' behavior is not adequately motivated, and (3) the randomness of the numbers generated by each participant is regarded as a stable trait of the participant, rather than as behavior of the participant. Recent behavioral variability research using operant conditioning procedures enables us to avoid these problems, and has produced evidence that random-like behavior can be learned. Results from this line of research may contribute to various other areas of psychology, such as modifying abnormally repetitive behavior, developing divergent thinking, exploring, and problem solving. But behavioral variability has at least two aspects: (1) "molecular" variability, including IRT and response topography, and (2) "molar" variability, including choice behavior, changes in play, going to various places, and building various kinds of forms. It is still unclear whether the same principle can explain both the molecular and molar levels of variability.

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Study objectives: The present study examined how the preference of humans between FR schedules and VR schedules changes after exposure to a specific schedule history. Design: A before-after design was used, in which the effects of the experimental treatment were estimated from the changed value from pre-test to post-test.Setting: Sessions were conducted individually in a small experimental booth. Participants: 27 undergraduate students. Independent variable: Schedule history: 14 participants were exposed to choice settings in which both terminal links were FR schedules, and 13 participants to choice settings in which both terminal links were VR schedules. Measures: Preferences were measured by concurrent-chain schedules of reinforcement. The 2 main dependent variables were relative response rates for the initial link that corresponded to the FR terminal link, and the number of trials in which the participants chose the FR terminal link. Results: The FR history and the VR history had different results. An FR history increased preference for VR schedules, whereas a VR history resulted in more variability. Conclusions: (1) prior exposure to a specific contingency may produce an oddity preference, and (2) FR schedules and VR schedules may have different effects on subsequent human performance.

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Study objectives: The present study examined whether or not the variability in color choice in pigeons could be generated by N -back reinforcement procedure. Participants: 4 homing pigeons. General procedure: 3 (red, green, cyan) or 4 (red, green, cyan, yellow) colored circles were presented on the front panel of the experimental chamber in a 3幼olumn by 6-row format. The position of each color was changed randomly in every session. Pigeons' pecks to the colored circles were reinforced on an N -back procedure in which the pigeons received food for each color choice that differed from the previous N rewarded choices. The value of N was increased from 1 to 3. Measure: Hr value, or a relative amount of information, was used as the index of response variability. This value varies between 0.0 and 1.0, with 0.0 indicating that all responses are perfectly predictable and 1.0 indicating maximum uncertainty. Results: When the value of N increased from 1 to 3, the number of colors that pigeons chose increased. The increment in the Hr value showed that pigeons' color choices became more variable in the 2- and 3-back conditions than in the 1-back condition. Conclusion: The results show that the variability in the color-choice response could be increased by the N back procedure.

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