Non-logical Simulation Model-Based Decision-Making Systems to Drive Self-motivation in Software Systems

This paper introduces a novel approach to decision-making systems in autonomous agents, leveraging the Independent Core Observer Model (ICOM) cognitive architecture. By synthesizing principles from Global Workspace Theory, Integrated Information Theory, the Computational Theory of Mind, Conceptual Dependency Theory, and Hierarchical Memory Theory together has been developed a framework that centers on simulated emotion-driven processes as the core mechanism for generating goals and motivations in independent agents. The ICOM system diverges from traditional logical reasoning models by incorporating non-logical, simulated emotion-based elements that mimic human-like decision-making capabilities, allowing us the ability to quantify the simulated emotional state of the machine and use that as the basis for decision-making and other motivational functions as it relates to that machine instance such as goal, actions or interest selection. We will review experimental results with robust and simplified systems and how that may or may not have implications for more sophisticated simulated emotionally aware software agents.