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Toward Self-Aware Robots.

Raja Chatila1, Erwan Renaudo1,2, Mihai Andries1,3

  • 1Institute of Intelligent Systems and Robotics, Sorbonne Université, CNRS, Paris, France.

Frontiers in Robotics and AI
|January 27, 2021
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Summary
This summary is machine-generated.

Robots and AI lack true understanding, acting like "zombies." This paper proposes self-awareness as key for artificial intelligence agents to comprehend their environment and actions, enabling genuine learning and cognition.

Keywords:
Markovian processesaffordancecognitive architecturedecision-makinghuman-robot interactionlearningplanningself-awareness

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Cognitive Science

Background:

  • Current robots and AI systems perform tasks without genuine understanding or self-awareness.
  • Deep-Learning AI lacks the ability to grasp the meaning of its inputs and outputs.
  • A theoretical framework for robot understanding, cognition, and self-awareness is missing.

Purpose of the Study:

  • To propose that agent self-awareness is a prerequisite for environmental understanding in artificial agents.
  • To explore the emergence of self-awareness from environmental interaction and self-other distinction.
  • To outline a cognitive architecture integrating perception, learning, interaction, and decision-making.

Main Methods:

  • Conceptual framework development.
  • Analysis of agent perception and environmental interaction.
  • Exploration of learning mechanisms for actions.
  • Examination of agent-human interaction dynamics.
  • Investigation of decision-making processes.
  • Design of a cognitive architecture.

Main Results:

  • Self-awareness emerges from an agent's understanding of its environment and its own embodiment.
  • Distinguishing self from environment is crucial for developing self-awareness.
  • A unified cognitive architecture can integrate key AI capacities.

Conclusions:

  • Achieving genuine understanding and cognition in AI requires developing self-awareness.
  • Self-awareness is not innate but emerges through interaction and learning.
  • This work provides a theoretical foundation for building more cognizant AI agents.