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Updated: May 28, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

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Published on: January 19, 2019

Preference-Based Representations for Collective Agency.

Nadav Amir1,2, Marieke van Vugt3, Maia Fraser4

  • 1Princeton Neuroscience Institute, Princeton University.

Topics in Cognitive Science
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational framework for multiagent systems, explaining how coordinated behavior arises from agents

Keywords:
Collective agencyGoal‐directed behaviorMental simulationPreference‐based learningReinforcement learningState representation learning

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Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Computational Neuroscience

Background:

  • Traditional reinforcement learning models focus on individual agent reward maximization, struggling with multiagent coordination.
  • Existing frameworks lack mechanisms to explain emergent collective behavior in systems with multiple agents.

Purpose of the Study:

  • To extend preference-based representations to a multiagent setting for explaining coordinated behavior.
  • To propose a cognitively plausible mechanism for acquiring, refining, and sharing goal-directed representations.

Main Methods:

  • Utilizing a computational framework of preference-based representations.
  • Extending single-agent models to a multiagent context.
  • Modeling coordinated behavior through subjective preferences and simulated experiences.

Main Results:

  • Demonstrated how coordinated behavior can emerge in multiagent systems from subjective preferences.
  • Showcased the role of simulated experiences in agent interaction and goal achievement.
  • Provided a framework for understanding collective agency.

Conclusions:

  • Preference-based representations offer a viable approach to modeling multiagent coordination.
  • Experience simulation mechanisms are key to understanding goal-directed behavior in bounded agents.
  • The framework contributes to ongoing discussions on individual and collective agency in AI and cognitive science.