Adaptive behavior in optimal sequential search.

Sequential decision making-making a decision where available options are encountered successively-is a hallmark of everyday life. Such decisions require deciding to accept or reject an alternative without knowing potential future options. Prior work focused on understanding choice behavior by developing decision models that capture human choices in such tasks. We investigated people's adaptive behavior in changing environments in light of their cognitive strategies. We present two studies in which we modified (a) outcome variance and (b) the time horizon and provide empirical evidence that people adapt to both context manipulations. Furthermore, we apply a recently developed threshold model of optimal stopping to our data to disentangle different cognitive processes involved in optimal stopping behavior. The results from Study 1 show that participants adaptively scaled the values of the sampling distribution to its variance, suggesting that the value of an option is perceived in relative rather than absolute terms. The results from Study 2 suggest that increasing the time horizon decreases the initial acceptance level, but less strongly than would be optimal. Furthermore, for longer sequences, participants more weakly adjusted this acceptance threshold over time than for shorter sequences. Further correlations between individual estimates in each condition indicate that individual differences between the participants' thresholds remain fairly stable between the conditions, pointing toward an additive effect of our manipulations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A cognitive category-learning model of rule abstraction, attention learning, and contextual modulation.

We introduce the Category Abstraction Learning (CAL) model, a cognitive framework formally describing category learning built on similarity-based generalization, dissimilarity-based abstraction, two attention learning mechanisms, error-driven knowledge structuring, and stimulus memorization. Our hypotheses draw on an array of empirical and theoretical insights connecting reinforcement and category learning. The key novelty of the model is its explanation of how rules are learned from scratch based on three central assumptions. (a) Category rules emerge from two processes of stimulus generalization (similarity) and its direct inverse (category contrast) on independent dimensions. (b) Two attention mechanisms guide learning by focusing on rules, or on the contexts in which they produce errors. (c) Knowing about these contexts inhibits executing the rule, without correcting it, and consequently leads to applying partial rules in different situations. The model is designed to capture both systematic and individual differences in a broad range of learning paradigms. We illustrate the model's explanatory scope by simulating several benchmarks, including the classic Six Problems, the 5-4 problem, and linear separability. Beyond the common approach of predicting average response probabilities, we also propose explanations for more recently studied phenomena that challenge existing learning accounts, regarding task instructions, individual differences in rule extrapolation in three different tasks, individual attention shifts to stimulus features during learning, and other phenomena. We discuss CAL's relation to different models, and its potential to measure the cognitive processes regarding attention, abstraction, error detection, and memorization from multiple psychological perspectives. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The influence of reward magnitude on stimulus memory and stimulus generalization in categorization decisions.

Reward magnitude is a central concept in most theories of preferential decision making and learning. However, it is unknown whether variable rewards also influence cognitive processes when learning how to make accurate decisions (e.g., sorting healthy and unhealthy food differing in appeal). To test this, we conducted 3 studies. Participants learned to classify objects with 3 feature dimensions into two categories before solving a transfer task with novel objects. During learning, we rewarded all correct decisions, but specific category exemplars yielded a 10 times higher reward (high vs. low). Counterintuitively, categorization performance did not increase for high-reward stimuli, compared with an equal-reward baseline condition. Instead, performance decreased reliably for low-reward stimuli. To analyze the influence of reward magnitude on category generalization, we implemented an exemplar-categorization model and a cue-weighting model using a Bayesian modeling approach. We tested whether reward magnitude affects (a) the availability of exemplars in memory, (b) their psychological similarity to the stimulus, or (c) attention to stimulus features. In all studies, the evidence favored the hypothesis that reward magnitude affects the similarity gradients of high-reward exemplars compared with the equal-reward baseline. The results from additional reward-judgment tasks (Studies 2 and 3) strongly suggest that the cognitive processes of reward-value generalization parallel those of category generalization. Overall, the studies provide insights highlighting the need for integrating reward- and category-learning theories. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Mood is linked to vowel type: the role of articulatory movements.

This study investigates the relation between vowel identity and emotional state. In Experiment 1, (pseudo)words were invented and articulated in a positive or negative mood condition. Subjects in a positive mood produced more words containing /i:/, a vowel involving the same muscle that is used in smiling--the zygomaticus major muscle (ZMM). Subjects in a negative mood produced more words containing /o:/, involving an antagonist of the ZMM--the orbicularis orbis muscle (OOM). We argue that the link between mood and vowel identity is related to orofacial muscle activity, which provides articulatory feedback to speakers on their emotional state. Experiment 2 tests this hypothesis more specifically. Participants rated the funniness of cartoons while repeatedly articulating either /i:/ (ZMM) or /o:/ (OOM). In line with our hypothesis, the cartoons were rated as funnier by subjects articulating /i:/ than by those articulating /o:/.