Precurrent contingencies: Behavior reinforced by altering reinforcement probability for other behavior

The present study explored the effects of a precurrent contingency in which one (precurrent) activity increased the reinforcement probability for another (current) activity. Four human subjects responded on a two-key computer mouse. Each right-key press was reinforced (points exchangeable for money) with .02 probability. In one condition (no precurrent contingency), pressing the left key had no scheduled consequence; in another condition (precurrent contingency), pressing the left key increased the reinforcement probability for right-key responding to .08 for 15 s. Initial exposure to the precurrent contingency resulted in acquisition of precurrent left-key responding for 3 subjects, but for the 4th subject a special contingency was required. Right-key responding occurred at a high stable rate across the conditions. Changeovers to left-key responding dropped to near zero when the precurrent contingency was absent and were maintained at enhanced levels when the precurrent contingency was present. Contacts with the left key consisted of short response runs. Right-key responses were more frequently emitted within 15 s of a left-key response when the precurrent contingency was present, an efficient adaptation to the contingency. Continued research on precurrent behavior may produce insights into complex phenomena such as autoclitics and self-control.     

Leaving patches: An investigation of a laboratory analogue

Five pigeons were trained on a procedure that has been used as a laboratory analogue to natural patch residence. Trials commenced with two responses available. One of these might provide a reinforcer if the patch was a prey patch; the other ended the residence time in the patch and, after a fixed travel time in blackout, produced another patch that might or might not provide a reinforcer. Patch residence also ended, and was followed by the same travel time, after a reinforcer was obtained or after a fixed maximum time was spent in the patch. The dependent variable was patch residence time, from the commencement of the patch to the time at which the subject emitted a response to exit from the patch or until the maximum patch residence time had elapsed. In Parts 1 to 3, the duration of the imposed travel time was varied from 0.25 to 16 s at three different probabilities (.05, .1, and .2) of food per second (λ) in prey patches. As reported in previous research, both increasing travel time and decreasing probabilities of reinforcers per second increased patch residence time. In Parts 4 to 7, the probability of prey trials (ρ) was varied in an irregular order from .1, through .2, .5, and .7, to .9 for different combinations of λ and travel time. Respectively, these were in Part 4, .05 per second and 0.25 s; in Part 5, .05 per second and 16 s; in Part 6, .2 per second and 0.25 s; and in Part 7, .2 per second and 16 s. A previously offered model, based on optimization assumptions, substantially and consistently underpredicted patch residence time. However, a modification of that model, which assumes that the subjects could not accurately discriminate the residence time that provided the minimum interreinforcer interval, described the data well. The same model also described previously reported residence times in a different species with a uniform distribution of prey-arrival times.     

Response acquisition under targeted percentile schedules: a continuing quandary for molar models of operant behavior.

The number of responses rats made in a "run" of consecutive left-lever presses, prior to a trial-ending right-lever press, was differentiated using a targeted percentile procedure. Under the nondifferential baseline, reinforcement was provided with a probability of .33 at the end of a trial, irrespective of the run on that trial. Most of the 30 subjects made short runs under these conditions, with the mean for the group around three. A targeted percentile schedule was next used to differentiate run length around the target value of 12. The current run was reinforced if it was nearer the target than 67% of those runs in the last 24 trials that were on the same side of the target as the current run. Programming reinforcement in this way held overall reinforcement probability per trial constant at .33 while providing reinforcement differentially with respect to runs more closely approximating the target of 12. The mean run for the group under this procedure increased to approximately 10. Runs approaching the target length were acquired even though differentiated responding produced the same probability of reinforcement per trial, decreased the probability of reinforcement per response, did not increase overall reinforcement rate, and generally substantially reduced it (i.e., in only a few instances did response rate increase sufficiently to compensate for the increase in the number of responses per trial). Models of behavior predicated solely on molar reinforcement contingencies all predict that runs should remain short throughout this experiment, because such runs promote both the most frequent reinforcement and the greatest reinforcement per press. To the contrary, 29 of 30 subjects emitted runs in the vicinity of the target, driving down reinforcement rate while greatly increasing the number of presses per pellet. These results illustrate the powerful effects of local reinforcement contingencies in changing behavior, and in doing so underscore a need for more dynamic quantitative formulations of operant behavior to supplement or supplant the currently prevalent static ones.     

The probabilistic import of illatives

It is not only overtly probabilistic illatives like makes it certain that but also apparently non-probabilistic ones like therefore that have probabilistic import. Illatives like therefore convey the meaning that the premise confers on the conclusion a probability not only greater than 0 but also greater than 1/2. But because they do not say whether that probability is equal to or less than 1, these illatives are appropriately called neutral.     

Choice behavior in transition: development of preference for the higher probability of reinforcement.

Ten acquisition curves were obtained from each of 4 pigeons in a two-choice discrete-trial procedure. In each of these 10 conditions, the two response keys initially had equal probabilities of reinforcement, and subjects' choice responses were about equally divided between the two keys. Then the reinforcement probabilities were changed so that one key had a higher probability of reinforcement (the left key in half of the conditions and the right key in the other half), and in nearly every case the subjects developed a preference for this key. The rate of acquisition of preference for this key was faster when the ratio of the two reinforcement probabilities was higher. For instance, acquisition of preference was faster in conditions with reinforcement probabilities of .12 and .02 than in conditions with reinforcement probabilities of .40 and .30, even though the pairs of probabilities differed by .10 in both cases. These results were used to evaluate the predictions of some theories of transitional behavior in choice situations. A trial-by-trial analysis of individual responses and reinforcers suggested that reinforcement had both short-term and long-term effects on choice. The short-term effect was an increased probability of returning to the same key on the one or two trials following a reinforcer. The long-term effect was a gradual increase in the proportion of responses on the key with the higher probability of reinforcement, an increase that usually continued for several hundred trials.     

Enumeration and simulation methods for 0–1 matrices with given marginals

Data in the form of zero-one matrices where conditioning on the marginals is relevant arise in diverse fields such as social networks and ecology; directed graphs constitute an important special case. An algorithm is given for the complete enumeration of the family of all zero-one matrices with given marginals and with a prespecified set of cells with structural zero entries. Complete enumeration is computationally feasible only for relatively small matrices. Therefore, a more useable Monte Carlo simulation method for the uniform distribution over this family is given, based on unequal probability sampling and ratio estimation. This method is applied to testing reciprocity of choices in social networks.The author wishes to thank Cajo ter Braak and John Birks for pointing out the relevance of this subject for ecology; and also Albert Verbeek and Ivo Molenaar, a referee, the Editor, and the Associate Editor for their comments. An earlier version of this paper was presented at the Stockholm Conference on Random Graphs and Applications (April 25–27, 1989), organized with financial support from the Swedish Council of Research in the Humanities and the Social Sciences.     

System and flexibility in law

Usually, rhetoric is supposed to provide a model of law which describes legal interactions as volitive, arbitrary, and void of any system. However, the Mainz School, founded by Theodor Viehweg, proves the contrary: without referring to any metaphysics, such as consensus or auditoire universel, it seeks to discover the systematic character and the more or less flexible structures of legal rhetoric.     

Basic and applied research on extinction bursts

Discontinuation of the contingency between a response and its reinforcer sometimes produces a temporary increase in the response before its rate decreases, a phenomenon called the extinction burst. Prior clinical and basic studies on the prevalence of the extinction burst provide highly disparate estimates. Existing theories on the extinction burst fail to account for the dynamic nature of this phenomenon, and the basic behavioral processes that control response bursting remain poorly understood. In this paper, we first review the basic and applied literature on the extinction burst. We then describe a recent refinement of the concatenated matching law called the temporally weighted matching law that appears to resolve the above-mentioned issues regarding the extinction burst. We present illustrative translational data based conceptually on the model. Finally, we discuss specific recommendations derived from the temporally weighted matching law regarding procedures clinicians could implement to potentially mitigate or prevent extinction bursts.     

基于群体水平评估的认知诊断模型开发与应用

本文开发了基于群体水平评估的认知诊断模型——G-AHM,采用Monte Carlo模拟方法探讨了模型的性能与表现,并探讨其在实践中的具体应用。研究发现：（1）新模型G-AHM不仅具有较高的边际判准率,还具有较好的模式判准率,且具有较强的稳健性,说明本研究开发的新模型基本合理、可行的。（2）与已有的具有较高效度的诊断结果比较发现：从认知状态、属性掌握概率与属性掌握比例三个方面,G-AHM模型所获得的群体诊断结果都与已有结果基本一致,即可以认为G-AHM方法获得的诊断结果也具有较高的效度。因此G-AHM模型在实际中是可行、可信的;且G-AHM方法中将认知状态与群体对属性的掌握概率信息相结合,可以更好的解释及分析被试的认知水平,提供的信息更具参考价值。     

不确定性容忍度对模糊决策中决策偏好的影响及其情景依赖性*

研究以Ellsberg选瓶任务为决策材料,探讨了不同任务特征下个体不确定性容忍度对模糊决策中决策偏好的影响。结果发现,获益情景下:高概率时高、低容忍度个体对模糊选项的选择无显著差异,均偏好模糊规避;中概率时低容忍度个体比高容忍度个体表现出更低程度的模糊规避,前者倾向于模糊中立,后者倾向于模糊规避;低概率时两者对模糊选项的选择无显著差异,均倾向于模糊中立。损失情景下:高概率时两者对模糊选项的选择无显著差异,均倾向于模糊寻求;中概率时低容忍度比高容忍度个体更偏好模糊寻求,前者倾向于模糊寻求,后者倾向于模糊中立;低概率时两者对模糊选项的选择无显著差异,均倾向于模糊规避。这表明,不确定性容忍度对模糊决策偏好产生作用,但这种作用会受到损益概率和损益结果的影响,具有情景依赖性。