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Embodied Intelligence: Smooth Coping in the Learning Intelligent Decision Agent Cognitive Architecture.

Christian Kronsted1,2, Sean Kugele2,3, Zachariah A Neemeh1,2

  • 1Department of Philosophy, University of Memphis, Memphis, TN, United States.

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Summary
This summary is machine-generated.

This study models smooth coping, skillful habituated action, in artificial agents. It proposes that smooth coping combines automatized actions with conscious control and sensorimotor processes for flexible adjustment.

Keywords:
LIDAaction selectionautomatizationcognitive architectureembodied cognitionglobal workspace theorysmooth coping

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Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Embodied Cognition

Background:

  • Everyday skilled actions, like walking or driving, are often performed as 'smooth coping,' characterized by habituation and reduced cognitive load.
  • Debate exists on whether smooth coping is purely automatized or involves intelligent flexibility, contrasting with deliberative thought.
  • Existing cognitive architectures often struggle to account for the subjective experience and flexibility of smooth coping.

Purpose of the Study:

  • To develop a fine-grained conceptual model for smooth coping in autonomous agents, both natural and artificial.
  • To demonstrate how smooth coping can be implemented in artificial intelligent agents using the LIDA cognitive architecture.
  • To explain the phenomenology of smooth coping by integrating theories of consciousness and embodied intelligence.

Main Methods:

  • Developed a conceptual model of smooth coping within the LIDA (Learning Intelligent Decision Agent) cognitive architecture.
  • Integrated LIDA's global workspace theory of consciousness and other psychological theories to model the subjective experience of smooth coping.
  • Introduced a new 'Automatized Action Selection' sub-module to LIDA to facilitate smooth coping mechanisms.

Main Results:

  • Proposed that smooth coping results from a sequence of automatized actions interspersed with conscious action selection and dorsal stream processing.
  • Demonstrated that non-conscious, automatized actions require occasional conscious cognition for skillful and flexible adjustments.
  • Highlighted the role of never-conscious dorsal stream information and sensorimotor processes in providing online adjustments during smooth coping.

Conclusions:

  • Smooth coping in artificial agents can be achieved by combining automatized actions with conscious control and embodied intelligence principles.
  • The LIDA architecture, with its conscious workspace and new sub-module, provides a viable framework for implementing smooth coping.
  • This model offers a detailed account of how both conscious and non-conscious processes contribute to skilled, embodied action.