Posts in Category: modeling

computational or mathematical models

Chapter: How can decision models decide to not decide? Modeling suspension in fast-and-frugal trees (FFTs)

Hansjörg Neth, Jelena Meyer

How can decision models decide to not decide? 
Modeling suspension in fast-and-frugal trees (FFTs)

Abstract

The phenomena of indecision and suspension loom large in both philosophy and psychology.  Whereas psychology discusses related phenomena in practical tasks and mostly pathological terms, philosophy strives for conceptual clarification and emphasizes the ubiquity and variety of suspension.

In this chapter, we use fast-and-frugal trees (FFTs) as a drosophila model for developing a positive account of suspension in decision-making.  Being designed for handling binary classification tasks, FFTs seem particularly ill-suited for accommodating a third stance.  But by replacing one decision outcome by a do not know category or adding it as a third option, we can adapt and extend the FFT framework to explore the causes and consequences of suspension.

Considering the distributions of decision outcomes and contrasting the performance of alternative models in terms of cost-benefit trade-offs illustrates the power of this methodology. Overall, a model-based approach provides surprising insights into the functions and mechanisms of suspension and serves as a productive tool for thinking.

Keywords

  • fast-and-frugal trees (FFTs), judgment and decision making (JDM), heuristics, binary classification, cost-benefit trade-offs, indecision, computer modeling, philosophy, machine learning, suspension

Reference

  • Neth, H., & Meyer, J. (2025). How can decision models decide to not decide?  Modeling suspension in fast-and-frugal trees (FFTs). In V. Wagner & A. Zinke (Eds.), Suspension in epistemology and beyond (pp. 286–303). New York, NY: Routledge.
    doi 10.4324/9781003474302-20

Related:  FFTrees: An R toolbox to create, visualize, and evaluate FFTs

Resources: 10.4324/9781003474302-20 | Download PDF |   Google Scholar

Paper: FFTrees: An R toolbox to create, visualize, and evaluate FFTs

If a decision tree that measures up very well on the performance criterion
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…

J. Ross Quinlan (1987), p. 498

An example of an FFT (created by FFTrees) predicting heard disease.

An example of an FFT predicting the risk of having heart disease.

Nathaniel Phillips, Hansjörg Neth, Jan Woike, Wolfgang Gaissmaier

FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees

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

To understand visual intelligence is to understand, in large part, who we are.
Donald D. Hoffmann (1998), p. XII
The body’s movements at this time scale provide an essential link between processes underlying elemental perceptual events
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.

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: Social influence and collective opinion formation

The rule is perfect: in all matters of opinion our adversaries are insane.
Mark Twain, Christian Science (1907, Book 1, Ch. 5)

Mehdi Moussaïd, Juliane E. Kämmer, Pantelis P. Analytis, Hansjörg Neth

Social influence and the collective dynamics of opinion formation

Abstract:  Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others.