Developing Self-Awareness in Robots via Inner Speech

Area of Science:

• Cognitive Science
• Robotics
• Artificial Intelligence

Background:

• Inner speech, a common human experience, plays vital roles in self-regulation and attention.
• Current robotics research rarely addresses inner speech or self-aware behaviors.
• Psychological models of inner speech offer a foundation for computational implementations.

Purpose of the Study:

• To review psychological models of inner speech.
• To propose a cognitive architecture for robots to simulate inner speech.
• To explore self-aware behaviors in artificial systems.

Main Methods:

• Literature review of psychological theories on inner speech.
• Conceptualization of a cognitive architecture for robotic inner speech.
• Simplified setup for outlining the proposed architecture.

Main Results:

• A comprehensive review of existing psychological models of inner speech.
• An outlined cognitive architecture for implementing inner speech in robots.
• Identification of potential for robots to exhibit self-aware behaviors.

Conclusions:

• Inner speech models can inform robotic self-awareness.
• The proposed architecture provides a framework for robotic introspection.
• Robotic implementation of inner speech could enhance autonomous behavior.