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Consciousness in a Self-Learning, Memory-Controlled, Compound Machine.

Robert Alan Brown1

  • 18 Foster Street, Mattapoisett, Massachusetts, MA 02739, USA

Neural Networks : the Official Journal of the International Neural Network Society
|March 29, 2003
PubMed
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This study introduces a compound machine that simulates consciousness by creating an internal environment. This machine can generate novel behaviors independently of external stimuli, mimicking biological systems.

Area of Science:

  • Artificial Intelligence
  • Cognitive Science
  • Robotics

Background:

  • Sensor/actuator machines rely on external environments for operation.
  • A lack of environmental input halts the behavioral output of these machines.
  • Existing systems lack the capacity for autonomous operation.

Purpose of the Study:

  • To develop a novel machine capable of functioning without an external environment.
  • To explore the creation of an 'illusion of an environment' within a machine.
  • To investigate methods for endowing machines with both instinctive and learned behaviors.

Main Methods:

  • Integration of sensor/sensor units to generate internal sensory data.
  • Addition of actuator/sensor and actuator/actuator units for enhanced functionality.

Related Experiment Videos

  • Distribution of predetermined and empirical memory cells for behavior control.
  • Modulation of machine behavior via cycle start and ramp signals, analogous to brain waves.

    • Main Results:

    • The compound machine successfully generated behavior without external environmental input.
    • The internal sensory stream created an 'illusion of an environment,' akin to consciousness.
    • Behavioral modification was achieved by altering memory cell activation signals.
    • The system demonstrated potential for both innate and acquired behavioral patterns.

    Conclusions:

    • Compound machines can achieve environmental independence through internal simulation.
    • The 'illusion of an environment' is a viable mechanism for machine consciousness.
    • Modulating memory cell activation signals offers a pathway to controlling complex machine behavior.
    • This architecture provides a foundation for advanced artificial intelligence and cognitive modeling.