Resistance to change and relapse of observing

Four experiments examined relapse of extinguished observing behavior of pigeons using a two-component multiple schedule of observing-response procedures. In both components, unsignaled periods of variable-interval (VI) food reinforcement alternated with extinction and observing responses produced stimuli associated with the availability of the VI schedule (i.e., S+). The components differed in the rate of food arranged (Rich = VI 30 s; Lean = VI 120 s). In Experiment 1, following baseline training, extinction of observing involved removal of both food and S+ deliveries, and reinstatement was examined by presenting either response-independent food or S+ deliveries. In Experiment 2, extinction involved removal of only food deliveries while observing responses continued to produce S+. Reinstatement was examined by delivering food contingent upon the first two food-key responses occurring in the presence of the S+. Experiment 3 assessed ABA renewal of observing by extinguishing food-key and observing responses in the presence of one contextual stimulus (i.e., B) and then returning to the original training context (i.e., A) during continued extinction. Experiment 4 examined resurgence by introducing food reinforcement for an alternative response during extinction, and subsequently removing that alternative source of food. Across experiments, relative resistance to extinction and relapse of observing tended to be greater in the component previously associated with the higher rate of primary reinforcement. Relapse of observing or attending to stimuli associated with primary reinforcement appears to be impacted by frequency of primary reinforcement in a manner similar to responding maintained directly by primary reinforcement.     

Rapid acquisition of bias in signal detection: dynamics of effective reinforcement allocation

We investigated changes in bias (preference for one response alternative) in signal detection when relative reinforcer frequency for correct responses varied across sessions. In Experiment 1, 4 rats responded in a two-stimulus, two-response identification procedure employing temporal stimuli (short vs. long houselight presentations). Relative reinforcer frequency varied according to a 31-step pseudorandom binary sequence and stimulus duration difference varied over two values across conditions. In Experiment 2, 3 rats responded in a five-stimulus, two-response classification procedure employing temporal stimuli. Relative reinforcer frequency was varied according to a 36-step pseudorandom ternary sequence. Results of both experiments were analyzed according to a behavioral model of detection. The model was extended to incorporate the effects of current and previous session reinforcer frequency ratios on current-session performance. Similar to findings with concurrent schedules, effects on bias of relative reinforcer frequency were highest for the current session. However, carryover from reinforcer ratios of previous sessions was evident. Generally, the results indicate that bias can come under control of frequent changes in relative reinforcer frequency in both identification and classification procedures.     

Instance‐based Learning: A General Model of Repeated Binary Choice

A common practice in cognitive modeling is to develop new models specific to each particular task. We question this approach and draw on an existing theory, instance‐based learning theory (IBLT), to explain learning behavior in three different choice tasks. The same instance‐based learning model generalizes accurately to choices in a repeated binary choice task, in a probability learning task, and in a repeated binary choice task within a changing environment. We assert that, although the three tasks are different, the source of learning is equivalent and therefore, the cognitive process elicited should be captured by one single model. This evidence supports previous findings that instance‐based learning is a robust learning process that is triggered in a wide range of tasks from the simple repeated choice tasks to the most dynamic decision making tasks. Copyright © 2010 John Wiley & Sons, Ltd.     

Soutien social perçu du supérieur,plafonnement de carrière et engagement affectif dans le secteur public camerounais

This research analyzes relation between the various types of career plateauing (objective, structural, content) and work emotional commitment. It also examines the influence of perceived social support from hierarchy on the different types of career plateauing, most especially its moderating role on the relation between the different types of career plateauing and emotional commitment. The results, which were obtained through data collected from 615 workers highlight that perceived social support from hierarchy limits and almost moderates negative relations between the different types of content plateauing (objective, content) and emotional commitment. Its direct effect on content plateauing is negative whereas the relation is positive with structural plateauing.     

Rapid decisions from experience

In many everyday decisions, people quickly integrate noisy samples of information to form a preference among alternatives that offer uncertain rewards. Here, we investigated this decision process using the Flash Gambling Task (FGT), in which participants made a series of choices between a certain payoff and an uncertain alternative that produced a normal distribution of payoffs. For each choice, participants experienced the distribution of payoffs via rapid samples updated every 50 ms. We show that people can make these rapid decisions from experience and that the decision process is consistent with a sequential sampling process. Results also reveal a dissociation between these preferential decisions and equivalent perceptual decisions where participants had to determine which alternatives contained more dots on average. To account for this dissociation, we developed a sequential sampling rank-dependent utility model, which showed that participants in the FGT attended more to larger potential payoffs than participants in the perceptual task despite being given equivalent information. We discuss the implications of these findings in terms of computational models of preferential choice and a more complete understanding of experience-based decision making.