Humans Adaptively Deploy Forward and Backward Prediction

Preprint: https://psyarxiv.com/wdbg4/

Paul B. Sharp and Eran Eldar

Brief summary of findings

The formation of predictions is essential to our ability to build models of the world and use them for intelligent decision-making. Here, we challenge the dominant assumption that humans only form forward predictions, which specify what future events are likely to follow a given present event. We demonstrate that in some environments, it is more efficient to use backward prediction, which specifies what present events are likely to precede a given future event. This is particularly the case in diverging environments, where possible future events outnumber possible present events. Correspondingly, in six preregistered experiments (N=1299), involving both simple decision-making and more challenging planning tasks, we find that humans engage in backward prediction in divergent environments, and in forward prediction in convergent environments. Thus, we establish that humans adaptively deploy forward and backward prediction in the service of efficient decision-making.

General structure of repository

• Each of the 4 studies has its own folder

  • Study_1
    • task
    • data
      • Main analysis in models.ipynb
    • graph_task
  • Study_2
    • task
    • data
      • Main analysis in models.ipynb
    • graph_task
  • Study_3
    • task
    • data
      • Main analysis in models.ipynb
    • graph_task
  • Study_4
    • task
    • data
      • Main analysis in models.ipynb
    • graph_task
  • Study_5
    • task
    • data
      • Main analysis in models.ipynb
    • graph_task
  • Study_6
    • analyses_main
    • analyses_followup

• All raw data is in a zipped file outside of study folder

OSF Repository

To see all preregistrations and data see DOI: 10.17605/OSF.IO/S286Z