Posts in Category: philosophy

the bigger picture: what? what for? what shall we do? why?

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: Rational task analysis (RTA)

Just as a scissors cannot cut paper without two blades,
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. 

Chapter: The cognitive basis of arithmetic

The truths about numbers are in us; but still we learn them.
G.W. Leibniz (1765), Nouveaux essais sur l’entendement humain, p. 85

[Copyright neth.de, 2010]:

Helen De Cruz, Hans Neth, Dirk Schlimm (2010). The cognitive basis of arithmetic.

Helen De Cruz, Hansjörg Neth, Dirk Schlimm

The cognitive basis of arithmetic

Overview:  Arithmetic is the theory of the natural numbers and one of the oldest areas of mathematics.  Since almost all other mathematical theories make use of numbers in some way or other, arithmetic is also one of the most fundamental theories of mathematics.  But numbers are not just abstract entities that are subject to mathematical ruminations — they are represented, used, embodied, and manipulated in order to achieve many different goals, e.g., to count or denote the size of a collection of objects, to trade goods, to balance bank accounts, or to play the lottery. Consequently, numbers are both abstract and intimately connected to language and to our interactions with the world.  In the present paper we provide an overview of research that has addressed the question of how animals and humans learn, represent, and process numbers.

Paper: A taxonomy of (practical vs. theoretical) actions

The solution to a problem changes the problem.
Peer’s Law

[Copyright neth.de, 2008]:

Hans Neth and Thomas Mueller (2008). Thinking by doing and doing by thinking: A taxonomy of actions. Paper presented at CogSci 2008.


Hansjörg Neth, Thomas Müller

Thinking by doing and doing by thinking: A taxonomy of actions

Abstract:  Taking a lead from existing typologies of actions in the philosophical and cognitive science literatures, we present a novel taxonomy of actions.