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Related Experiment Videos

Types of planning: can artificial intelligence yield insights into prefrontal function?

J A Hendler1

  • 1Department of Computer Science, University of Maryland, College Park 20742, USA.

Annals of the New York Academy of Sciences
|December 15, 1995
PubMed
Summary

Artificial intelligence (AI) models are being developed to understand complex planning behaviors, mimicking human prefrontal cortex functions. These AI systems utilize hierarchical memory schemata and parallel processing for adaptive, long-term behavior in robotic systems.

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Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Robotics

Background:

  • The human prefrontal cortex handles complex planning.
  • Understanding computational models of planning is crucial for AI development.

Purpose of the Study:

  • To explore features of artificial intelligence (AI) planning models.
  • To explain how AI systems tackle problems similar to human prefrontal cortex functions.
  • To examine information-processing constraints for computational planning models.

Main Methods:

  • Described AI models using hierarchical schemata for memory representation.
  • Detailed how activation spreading influences schema selection and monitoring.
  • Incorporated environmental stimuli affecting schema processing.

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  • Presented a parallel processing model with multiple schemata of varying temporal extent.

    • Main Results:

    • AI models converge on a framework for planned behavior.
    • A specific AI planning model demonstrates effective robotic system behaviors.
    • The model integrates memory, hierarchical representation, and parallel processing.

    Conclusions:

    • AI planning models offer insights into cognitive processes.
    • Computational approaches can replicate complex planning behaviors.
    • The presented model shows promise for advanced robotic applications.