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Agents often undermatch choices, favoring poorer options. This study explains undermatching by proposing agents minimize cognitive cost (policy complexity) alongside maximizing reward, a theory supported by mouse and Parkinson's disease patient data.

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Area of Science:

  • Behavioral economics
  • Cognitive neuroscience
  • Reinforcement learning

Background:

  • The matching law predicts equal allocation of choices to rewards, but undermatching (bias towards poorer options) is common.
  • Existing theories lack a strong normative justification for the widespread phenomenon of undermatching.
  • Cognitive cost, or policy complexity, has not been fully integrated into models of choice behavior.

Purpose of the Study:

  • To provide a normative justification for undermatching by incorporating cognitive cost minimization.
  • To develop a theory where agents balance reward maximization with policy complexity reduction.
  • To test predictions of this theory using behavioral data from mice and Parkinson's disease patients.

Main Methods:

  • Formalized policy complexity as mutual information between actions and environmental states.
  • Developed a theoretical model where capacity-constrained agents can only undermatch or perfectly match.
  • Collected and analyzed behavioral data from male mice under varying task conditions.
  • Examined choice behavior in male and female Parkinson's disease patients in relation to dopamine levels.

Main Results:

  • The proposed theory accurately predicts that agents will undermatch or perfectly match, but not overmatch.
  • Identified specific task conditions that exacerbate undermatching in mice.
  • Observed a reduction in undermatching with increased dopamine levels in Parkinson's disease patients.
  • Demonstrated a neural correlate: policy complexity, and thus undermatching, is modulated by dopamine.

Conclusions:

  • Minimizing policy complexity alongside reward maximization provides a robust explanation for undermatching.
  • Capacity constraints on policy compression are key to understanding undermatching.
  • Dopamine plays a crucial role in cognitive resource allocation, influencing policy complexity and choice behavior.
  • The findings offer a unified framework for understanding choice behavior across different agents and conditions.