AGI systems should be built around an agent's internal needs and goals as the core driver of learning and decision-making, rather than treating intelligence as separate from motivation.
This paper proposes a cognitive architecture for artificial general intelligence that models the psyche as an operating system managing an agent's needs, sensations, and actions. The approach formalizes AGI as an optimization problem where agents learn through experience to satisfy needs while managing uncertainty and minimizing existential risks.