Humans rationally balance detailed and temporally abstract world models
2025

Humans Balance Detailed and Abstract World Models

Sample size: 100 publication Evidence: high

Author Information

Author(s): Ari E. Kahn, Nathaniel D. Daw

Primary Institution: Princeton University

Hypothesis

Do individuals dynamically adjust their reliance on the Successor Representation based on the predictability of their environment?

Conclusion

Participants adaptively employ a mix of decision strategies, including model-based learning and the Successor Representation, which varies based on the predictability of future states.

Supporting Evidence

  • Participants exhibited a significant win-stay-lose-shift pattern in their choices based on previous rewards.
  • Behavior was best explained by a mixture of model-based and Successor Representation strategies.
  • Reliance on the Successor Representation increased when future state occupancy was stable.

Takeaway

People use different strategies to make decisions, sometimes thinking in detail and other times using simpler, quicker methods, depending on how predictable things are.

Methodology

Participants completed a two-stage Markov decision task where they chose between islands and boats to maximize rewards.

Limitations

The study did not distinguish between linear reinforcement learning and a mixture of separate agents for decision-making.

Participant Demographics

Participants were 51 male, 44 female, and aged 18 to 68 years, with a mean age of 36.19.

Statistical Information

P-Value

p<1eāˆ’21

Confidence Interval

95% CI = +/āˆ’0.101

Statistical Significance

p<1eāˆ’21

Digital Object Identifier (DOI)

10.1038/s44271-024-00169-3

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