Active information seeking using the Approximate Number System
- Jinjing (Jenny) Wang, Rutgers University, Newark, New Jersey, United States
- Elizabeth Bonawitz, Psychology, Rutgers University - Newark, Newark, New Jersey, United States
AbstractHuman adults share the ability to approximate large quantities without counting with newborn infants and non-human species. This ability is supported by the Approximate Number System (ANS) - a primitive and domain-specific cognitive system that supports noisy numerical decisions. How does the ANS support active exploratory decisions? Using a numerical comparison task, we found that the amount of active information seeking does not simply increase as the decision becomes more difficult. Instead, there seems to be an inverted U-shaped relationship between trial difficulty and how much one chooses to seek information. Additionally, this effect is not modulated by participants’ performance, suggesting that participants’ exploratory decisions based on ANS representations are driven by the utility of information seeking actions.
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