Posts in Category: cognitive science
the interdisciplinary study of cognition and behavior
Paper: FFTrees: An R toolbox to create, visualize, and evaluate FFTs
is nevertheless totally incomprehensible to a human expert, can it
be described as knowledge? Under the common-sense definition of this term
as material that might be assimilated and used by human beings, it is not…
Nathaniel Phillips, Hansjörg Neth, Jan Woike, Wolfgang Gaissmaier
FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees
An example of an FFT predicting the risk of having heart disease.
Abstract: Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available toolbox that allows anyone to easily create, visualize, and evaluate FFTs. We fill this gap by introducing the R package FFTrees.
Paper: Visual working memory resources as item activation
Donald D. Hoffmann (1998), p. XII
and those involved in symbol manipulation and the organization of complex behaviors.
Ballard et al. (1997), p. 723
Bella Z. Veksler, Rachel Boyd, Christopher W. Myers, Glenn Gunzelmann, Hansjörg Neth, Wayne D. Gray
Visual working memory resources are best characterized as dynamic, quantifiable mnemonic traces
An example stimulus used in the paradigm of repeated serial search.
Abstract: Visual working memory (VWM) is a construct hypothesized to store a small amount of accurate perceptual information that can be brought to bear on a task. Much research concerns the construct’s capacity and the precision of the information stored. Two prominent theories of VWM representation have emerged: slot-based and continuous-resource mechanisms. Prior modeling work suggests that a continuous resource that varies over trials with variable capacity and a potential to make localization errors best accounts for the empirical data. Questions remain regarding the variability in VWM capacity and precision. Using a novel eye-tracking paradigm, we demonstrate that VWM facilitates search and exhibits effects of fixation frequency and recency, particularly for prior targets. Whereas slot-based memory models cannot account for the human data, a novel continuous-resource model does capture the behavioral and eye tracking data, and identifies the relevant resource as item activation.
Paper: Rational task analysis (RTA)
a theory of thinking and problem solving cannot predict behavior
unless it encompasses both an analysis of the structure of task environments
and an analysis of the limits of rational adaptation to task requirements.
(Newell & Simon, 1972, p. 55)
Hansjörg Neth, Chris R. Sims, Wayne D. Gray
Rational task analysis: A methodology to benchmark bounded rationality
Abstract: How can we study bounded rationality? We answer this question by proposing rational task analysis (RTA)—a systematic approach that prevents experimental researchers from drawing premature conclusions regarding the (ir-)rationality of agents. RTA is a methodology and perspective that is anchored in the notion of bounded rationality and aids in the unbiased interpretation of results and the design of more conclusive experimental paradigms.
Paper: Melioration as rational choice
Melioration (…) is the dynamic process controlling allocation of time across response alternatives.
Herrnstein & Vaughan (1980). Melioration and behavioral allocation, p. 143+172
Chris R. Sims, Hansjörg Neth, Robert A. Jacobs, Wayne D. Gray
Melioration as rational choice: Sequential decision making in uncertain environments
Abstract: Melioration — defined as choosing a lesser, local gain over a greater longer term gain — is a behavioral tendency that people and pigeons share. As such, the empirical occurrence of meliorating behavior has frequently been interpreted as evidence that the mechanisms of human choice violate the norms of economic rationality. In some environments, the relationship between actions and outcomes is known. In this case, the rationality of choice behavior can be evaluated in terms of how successfully it maximizes utility given knowledge of the environmental contingencies. In most complex environments, however, the relationship between actions and future outcomes is uncertain and must be learned from experience. When the difficulty of this learning challenge is taken into account, it is not evident that melioration represents suboptimal choice behavior.