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Affective Episodic Memory System for Virtual Creatures: The First Step of Emotion-Oriented Memory.

Luis Martin¹, Jonathan H Rosales², Karina Jaime¹

¹Department of Computer Science, Center for Research and Advanced Studies of the National Polytechnic Institute, Zapopan 45019, Mexico.

Computational Intelligence and Neuroscience

|November 1, 2021

Summary

This study introduces a novel computational model integrating episodic memory and emotions for artificial intelligence. This emotional episodic model enhances learning and decision-making in virtual creatures.

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Area of Science:

Cognitive Science
Artificial Intelligence
Computational Neuroscience

Background:

Episodic memory and emotions are vital for human cognition and learning.
Existing cognitive architectures often isolate memory and emotion processing.
A gap exists in models that directly link affective evaluations to episodic memories.

Purpose of the Study:

To propose a computational model integrating episodic memory and emotion processing.
To focus on the affective evaluation of episodic memories based on cognitive science principles.
To incorporate this model into the Cuáyóllótl cognitive architecture for cybernetic entities.

Main Methods:

Developing a computational model grounded in neuroscience and psychology.
Designing model components and processes based on cognitive science evidence.
Integrating the emotional episodic model into a cognitive architecture (Cuáyóllótl).

Main Results:

Case studies demonstrate the model's validity and relevance.
Integration of emotions and memory significantly impacts virtual creature behavior.
The model enhances learning and modifies decision-making processes in virtual agents.

Conclusions:

The proposed model effectively integrates episodic memory and emotions.
This integration is crucial for developing human-like artificial intelligence.
The model shows promise for enhancing learning and adaptive behavior in robots and virtual creatures.