Researchers propose a global broadcasting system for essential information in the brain to be used by robotic structures; specifically, they utilize cognitive robotics in Global Workspace Theory (GWT) to simulate episodic memory in conscious systems.
Furthermore, researchers used important aspects of cognitive robotics, such as artificial neural networks, to simulate a ‘global workspace’ in early models of Global Workspace Theory (GWT).
In addition, researchers have improved their models by adding advanced mechanisms to help retrieve personal experiences and their time and place, thereby enhancing episodic memory understanding.
This typically involves researchers creating long-term stores for specific events, retrieving them, and adding them to the global workspace. Attention and salience enhance the link between consciousness and episodic memory. Researchers study how attentional mechanisms, from both sensory input and goal-driven inputs, control the retrieval of episodic memories for conscious processing.
In addition, researchers subject these simulated robot agents to a series of tasks that attempt to test their memory recall capabilities, their attentional selectivity, and, ultimately, their ability to bring prior experience into their current decision-making frameworks..
Evaluating these implementations is difficult, requiring the construction of objective measures to determine the degree to which a cognitive robotics system learns behaviors congruent with conscious awareness and episodic recall.
Research is vital for understanding consciousness and memory, aiding in cognitive robotic development. Developers should use strict verification methods tested with human data.
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