In each of three experiments, a single group of participants received a sequence of trials involving pictures of a variety of foods presented individually or in pairs. Participants were required to predict in which trials the food would lead to a hypothetical allergic reaction. The different trials involved blocking, A+ AX+, and a simple discrimination, BY- CY+, in which each letter stands for a different food. Training trials were followed by a test in which participants were asked to predict how likely each kind of food would be followed by the allergic reaction. The principal purpose of the experiments was to determine how the redundant cue from blocking, X, would be judged relative to the redundant cue from the simple discrimination, Y. In contrast to predictions from currently influential theories of associative learning, X was regarded as a better predictor for the allergic reaction than Y.

In this article, the authors report 2 experiments that investigated the sources of information used in transfer and nontransfer tasks in artificial grammar learning. Multiple regression analyses indicated that 2 types of information about repeating elements were crucial for performance in both tasks: information about the repetition of adjacent elements and information about repetition of elements in the whole item. Similarity of test items to specific training items and chunk information influenced participants' judgments only in nontransfer tasks.

For some decades, failures to find extinction of inhibition through unpaired presentations of the inhibitor were taken as evidence against conceptualizing inhibition as the symmetrical counterpart of excitation. Recently, however, our group has demonstrated successful extinction of inhibition in human causal learning. In two experiments, we replicated and strengthened this finding by using an outcome continuum that could take on negative, neutral, or positive values. In contrast, the use of a dichotomous outcome continuum (either neutral or positive) resulted in the well-known nonoccurrence of extinction. Extinction of inhibition through the pairing of inhibitors with neutral outcomes was assessed by (1) comparing the (presumably) extinguished inhibitor with a second inhibitor that had not been presented with a neutral outcome in the extinction stage, and (2) demonstrating the course of extinction in participants' predictions.

Two experiments are presented that test the predictions of two associative learning models of Artificial Grammar Learning. The two models are the simple recurrent network (SRN) and the competitive chunking (CC) model. The two experiments investigate acquisition of different types of knowledge in this task: knowledge of frequency and novelty of stimulus fragments (Experiment 1) and knowledge of letter positions, of small fragments, and of large fragments up to entire strings (Experiment 2). The results show that participants acquired all types of knowledge. Simulation studies demonstrate that the CC model explains the acquisition of all types of fragment knowledge but fails to account for the acquisition of positional knowledge. The SRN model, by contrast, accounts for the entire pattern of results found in the two experiments.

In two experiments we investigated recognition and classification judgements using an artificial grammar learning paradigm. In Experiment 1, when only new test items had to be judged, analysis of z-transformed receiver operating characteristics (z-ROCs) revealed no differences between classification and recognition. In Experiment 2, where we included old test items, z-ROCs in the two tasks differed, suggesting that judgements relied on different types of information. The results are interpreted in terms of heuristics that people use when making classification and recognition judgements.