Results 1  10
of
19
TOWARD A UNIFIED THEORY OF DECISION CRITERION LEARNING IN PERCEPTUAL CATEGORIZATION
 JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR
, 2002
"... Optimal decision criterion placement maximizes expected reward and requires sensitivity to the category base rates (prior probabilities) and payoffs (costs and benefits of incorrect and correct responding). When base rates are unequal, human decision criterion is nearly optimal, but when payoffs are ..."
Abstract

Cited by 26 (12 self)
 Add to MetaCart
Optimal decision criterion placement maximizes expected reward and requires sensitivity to the category base rates (prior probabilities) and payoffs (costs and benefits of incorrect and correct responding). When base rates are unequal, human decision criterion is nearly optimal, but when payoffs are unequal, suboptimal decision criterion placement is observed, even when the optimal decision criterion is identical in both cases. A series of studies are reviewed that examine the generality of this finding, and a unified theory of decision criterion learning is described (Maddox & Dodd, 2001). The theory assumes that two critical mechanisms operate in decision criterion learning. One mechanism involves competition between reward and accuracy maximization: The observer attempts to maximize reward, as instructed, but also places some importance on accuracy maximization. The second mechanism involves a flatmaxima hypothesis that assumes that the observer’s estimate of the rewardmaximizing decision criterion is determined from the steepness of the objective reward function that relates expected reward to decision criterion placement. Experiments used to develop and test the theory require each observer to complete a large number of trials and to participate in all conditions of the experiment. This provides maximal control over the reinforcement history of the observer and allows a focus on individual behavioral profiles. The theory is applied to decision criterion learning problems that examine category discriminability, payoff matrix multiplication and addition effects, the optimal classifier’s independence assumption, and different types of trialbytrial feedback. In every case the theory provides a good account of the data, and, most important, provides useful insights into the psychological processes involved in decision criterion learning.
On the Relation Between Baserate and CostBenefit Learning in Simulated Medical Diagnosis
, 2001
"... Observers completed a series of simulated medical diagnosis tasks that differed in category discriminability and baserate/costbenefit ratio. Point, accuracy, and decision criterion estimates were closer to optimal (a) for category d' = 2.2 than for category d' = 1.0 or 3.2, (b) when baserates, as ..."
Abstract

Cited by 17 (13 self)
 Add to MetaCart
Observers completed a series of simulated medical diagnosis tasks that differed in category discriminability and baserate/costbenefit ratio. Point, accuracy, and decision criterion estimates were closer to optimal (a) for category d' = 2.2 than for category d' = 1.0 or 3.2, (b) when baserates, as opposed to costbenefits were manipulated, and (c) when the cost of an incorrect response resulted in no point loss (nonnegative cost) as opposed to a point loss (negative cost). These results support the "flatmaxima" (von Winterfeldt & Edwards, 1982) and COmpetition Between Reward and Accuracy (COBRA; Maddox & Bohil, 1998a) hypotheses. A hybrid model that instantiated simultaneously both hypotheses was applied to the data. The model parameters indicated that (a) the rewardmaximizing decision criterion quickly approached the optimal criterion, (b) the importance placed on accuracy maximization early in learning was larger when the cost of an incorrect response was negative as opposed to nonnegative, and (c) by the end of training the importance placed on accuracy was equal for negative and nonnegative costs.
Costs and benefits in perceptual categorization
 Memory & Cognition
"... conditions, and costs were either zero or nonzero. The costbenefit structures were selected so that performance across conditions was equivalent with respect to the optimal classifier. Each observer completed several blocks of trials in each of the experimental conditions, and a series of nested m ..."
Abstract

Cited by 13 (11 self)
 Add to MetaCart
conditions, and costs were either zero or nonzero. The costbenefit structures were selected so that performance across conditions was equivalent with respect to the optimal classifier. Each observer completed several blocks of trials in each of the experimental conditions, and a series of nested models were applied to the individual observer data from all conditions. In general, performance became more nearly optimal as observers gained experience with the costbenefit structures, but performance reached asymptote at a suboptimal level. Observers behaved differently in the zero and nonzero cost conditions, performing consistently worse when costs were nonzero. A test of the hypothesis that observers weight costs more heavily than benefits was inconclusive. Some aspects of the data supported this differential weighting hypothesis, but others did not. Implications for current theories of costbenefit learning are discussed. Everyday we make important decisions based on uncertain information. For example, we might decide to “bring ” or “not bring ” an umbrella to work based solely on uncertain predictors of rain, like the degree of overcast. This is a categorization problem because there are many degrees of overcast that one might observe, but
Category discriminability, baserate, and payoff effects in perceptual organization
 Perception & Psychophysics
, 2001
"... (i.e., d ¢ level), base rates, and payoffs was examined. Baserate and payoff manipulations across two category discriminabilities allowed a test of the hypothesis that the steepness of the objective reward function affects performance (i.e., the flatmaxima hypothesis), as well as the hypothesis th ..."
Abstract

Cited by 10 (7 self)
 Add to MetaCart
(i.e., d ¢ level), base rates, and payoffs was examined. Baserate and payoff manipulations across two category discriminabilities allowed a test of the hypothesis that the steepness of the objective reward function affects performance (i.e., the flatmaxima hypothesis), as well as the hypothesis that observers combine baserate and payoff information independently. Performance was (1) closer to optimal for the steeper objective reward function, in line with the flatmaxima hypothesis, (2) closer to optimal in baserate conditions than in payoff conditions, and (3) in partial support of the hypothesis that baserate and payoff knowledge is combined independently. Implications for current theories of baserate and payoff learning are discussed.
Feedback effects on cost–benefit learning in perceptual categorization
 Memory & Cognition
, 2001
"... Two experiments were conducted in which the effects of different feedback displays on decision criterion learning were examined in a perceptual categorization task with unequal cost–benefits. In Experiment 1, immediate versus delayed feedback was combined factorially with objective versus optimal cl ..."
Abstract

Cited by 8 (5 self)
 Add to MetaCart
Two experiments were conducted in which the effects of different feedback displays on decision criterion learning were examined in a perceptual categorization task with unequal cost–benefits. In Experiment 1, immediate versus delayed feedback was combined factorially with objective versus optimal classifier feedback. Immediate versus delayed feedback had no effect. Performance improved significantly over blocks with optimal classifier feedback and remained relatively stable with objective feedback. Experiment 2 used a withinsubjects design that allowed a test of modelbased instantiations of the flatmaxima (von Winterfeldt & Edwards, 1982) and competition between reward and accuracy (Maddox & Bohil, 1998a) hypotheses in isolation and of a hybrid model that incorporated assumptions from both hypotheses. The modelbased analyses indicated that the flatmaxima model provided a good description of early learning but that the assumptions of the hybrid model were necessary to account for later learning. An examination of the hybrid model parameters indicated that the emphasis placed on accuracy maximization generally declined with experience for optimal classifier feedback but remained high, and fairly constant for objective classifier feedback. Implications for cost–benefit training are discussed.
On the generality of optimal versus objective classifier feedback effects on decision criterion learning in perceptual categorization
 Memory & Cognition
"... Biased category payoff matrices engender separate reward and accuracymaximizing decision criteria. Although instructed to maximize reward, observers use suboptimal decision criteria that place greater emphasis on accuracy than is optimal. This study compared objective classifier feedback (the obj ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
Biased category payoff matrices engender separate reward and accuracymaximizing decision criteria. Although instructed to maximize reward, observers use suboptimal decision criteria that place greater emphasis on accuracy than is optimal. This study compared objective classifier feedback (the objectively correct response) with optimal classifier feedback (the optimal classifier’s response) at two levels of category discriminability when zero or negative costs accompanied incorrect responses for two payoff matrix multiplication factors. Performance was superior for optimal classifier feedback relative to objective classifier feedback for both zero and negative cost conditions, especially when category discriminability was low, but the magnitude of the optimal classifier advantage was approximately equal for zero and negative cost conditions. The optimal classifier feedback performance advantage did not interact with the payoff matrix multiplication factor. Modelbased analyses suggested that the weight placed on
A Theoretical Framework for Understanding the Effects of Simultaneous BaseRate and Payoff . . .
, 2003
"... ..."
Journal of Expenraeal Psychology Copyrighl 20D1 by Ih American Psychoiogc. Assocatioa. Inc, Learning, Mmor, nnd Cogmteon 0277393/01P$5.fJ DO1 ID 1037//0278739327.6.1367 200L o. 2:7. No. 6. [3671384
, 2001
"... this article. We also thank Lofilei Carderhas and Robert F. zwin for help with data collection ..."
Abstract
 Add to MetaCart
this article. We also thank Lofilei Carderhas and Robert F. zwin for help with data collection