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  2. A Predictive Processing Framework For Joint Action And Communication.
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A predictive processing framework for joint action and communication.

Giovanni Pezzulo1, Günther Knoblich2, Domenico Maisto1

  • 1Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.

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|March 14, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Humans coordinate actions and communicate using agent-neutral models, predicting collective outcomes rather than individual ones. This new framework explains joint action and communication by focusing on shared predictive processing.

Keywords:
Agent-neutral modelsCommunicationCoordinationJoint actionPredictive processing

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Area of Science:

  • Cognitive Neuroscience
  • Social Psychology
  • Computational Neuroscience

Background:

  • Human joint action and communication are complex abilities requiring individuals to transcend personal perspectives for shared goals.
  • Existing frameworks often focus on agent-specific models, which may not fully capture the collaborative nature of human interaction.
  • Understanding the computational underpinnings of social cognition is crucial for explaining human cooperation.

Purpose of the Study:

  • To propose a novel theoretical framework for explaining human joint action and communication.
  • To extend predictive processing architectures from individual cognition to multiagent interactive settings.
  • To introduce the concept of agent-neutral models in understanding collaborative behaviors.

Main Methods:

  • Development of a theoretical framework based on predictive processing principles.
  • Extension of individual predictive processing to multiagent, interactive contexts.
  • Formulation of three key claims regarding agent-neutral models in joint action and communication.

Main Results:

  • Proposed that co-agents utilize agent-neutral predictive frameworks during joint action.
  • Hypothesized that agent-neutral models are updated interactively through communication, shaping predictions.
  • Suggested that agent-neutral models facilitate dynamic role allocation in joint actions.

Conclusions:

  • The agent-neutral predictive processing framework offers a new perspective on human sociality.
  • This framework integrates theories of joint action and communication with computational neuroscience.
  • Further experimental research is needed to validate the proposed claims and the framework's efficacy.