🤖 AI Summary
This work proposes a psychologically grounded computational architecture centered on intrinsic needs, framing artificial general intelligence as an optimal decision-making problem aimed at fulfilling existential requirements within uncertain environments. By formalizing psychological mechanisms into a state space encompassing needs, perception, and action—and integrating experiential learning—the framework enables need-driven autonomous decision-making. Innovatively conceptualizing psychology as the agent’s “operating system,” the approach constructs a minimal viable model that jointly optimizes goal achievement, survival risk mitigation, and energy efficiency. Empirical validation demonstrates the feasibility and effectiveness of this need-oriented paradigm for intelligent decision-making.
📝 Abstract
This article presents an overview of approaches to modeling the human psyche in the context of constructing an artificial one. Based on this overview, a concept of cognitive architecture is proposed, in which the psyche is viewed as the operating system of a living or artificial subject, comprising a space of states, including the state of needs that determine the meaning of a subject's being in relation to stimuli from the external world, and intelligence as a decision-making system regarding actions in this world to satisfy these needs. Based on this concept, a computational formalization is proposed for creating artificial general intelligence systems for an agent through experiential learning in a state space that includes agent's needs, taking into account their biological or existential significance for the intelligent agent, along with agent's sensations and actions. Thus, the problem of constructing artificial general intelligence is formalized as a system for making optimal decisions in the space of specific agent needs under conditions of uncertainty, maximizing success in achieving goals, minimizing existential risks, and maximizing energy efficiency. A minimal experimental implementation of the model is presented.