A Novel Model of Narrative Memory for Conscious Agents

Abstract

The aim of Artificial General Intelligence (AGI) is to build machines with cognitive abilities on par with humans. These abilities include sensing, reasoning, decision-making, and social interaction. Although great strides have been achieved in creating intelligent agents that can observe and form opinions about their surroundings, problems still arise when it comes to their ability to reason and make decisions. The lack of a narrative structure inside these intelligent beings is a major drawback. This study suggests creating a narrative memory model with a dedicated module for use by self-aware agents. The model incorporates narrative memory to improve the agent's perception, understanding, and decision-making capabilities. The conscious agent will be able to create, store, and recall narrative-like representations of prior experiences with the help of the narrative memory module. To help the agent make sense of its surroundings, this narrative structure will give a method for categorizing and linking data. The agent will be able to recognize patterns, determine causal linkages, and extrapolate future outcomes by drawing on its narrative memory. There are several benefits to incorporating narrative memory into the brain of a self-aware agent. First, it'll give the agent a richer context from which to draw insights and make judgments. Second, the agent's perception and interpretation of complicated circumstances, as well as its general reasoning abilities, will be bolstered by the narrative memory module. Thirdly, the agent will be able to develop over time by absorbing new information and incorporating it into its preexisting narrative memory. This study uses a narrative memory-based approach to close the gap between conscious agents and human-like reasoning. The goal of this study is to improve the cognitive capacities of conscious agents by giving them the capacity to create and employ narrative memories, thus facilitating more nuanced perception, comprehension, and decision-making. The findings of this study could have far-reaching implications for the fields of artificial intelligence, robotics, and human-computer interaction by accelerating the creation of AGI systems with human-level cognitive capacities.