Referensi ini mendukung integrasi konsep Id, Ego, Superego, dan meta-kognisi dalam arsitektur AGI.
Freud, S. (1923). The Ego and the Id. Hogarth Press.
 Baars, B. J. (1997). In the Theater of Consciousness: The Workspace of the Mind. Oxford University Press.
 Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
 Minsky, M. (2006). The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind. Simon & Schuster.
 Friston, K. (2010). "The Free-Energy Principle: A Unified Brain Theory?" Nature Reviews Neuroscience, 11(2), 127-138.
7.3. Referensi tentang Filsafat Kesadaran dan Intuisi dalam AI
Referensi ini mendukung eksplorasi konsep kesadaran (consciousness) dan intuisi (Bashirah) dalam pengambilan keputusan AGI.
Chalmers, D. J. (1996). The Conscious Mind: In Search of a Fundamental Theory. Oxford University Press.
 Tononi, G. (2008). "Consciousness as Integrated Information: A Provisional Manifesto." The Biological Bulletin, 215(3), 216-242.
 Nagel, T. (1974). "What is it Like to Be a Bat?" The Philosophical Review, 83(4), 435-450.
 Gopnik, A. (2020). The Philosophical Baby: What Children's Minds Tell Us About Truth, Love, and the Meaning of Life. Farrar, Straus and Giroux.
 Dehaene, S. (2014). Consciousness and the Brain: Deciphering How the Brain Codes Our Thoughts. Viking.
7.4. Referensi tentang Teori Keputusan Probabilistik dan Bayesian Reasoning
Referensi ini mendukung penerapan Bayesian Decision Theory dalam pengambilan keputusan AGI, terutama dalam dilema moral seperti Trolley Problem.
Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann.
 Jaynes, E. T. (2003). Probability Theory: The Logic of Science. Cambridge University Press.
 Berger, J. O. (2013). Statistical Decision Theory and Bayesian Analysis (2nd Edition). Springer.
 Tversky, A., & Kahneman, D. (1981). "The Framing of Decisions and the Psychology of Choice." Science, 211(4481), 453-458.
 Griffiths, T. L., Kemp, C., & Tenenbaum, J. B. (2008). "Bayesian Models of Cognition." Cambridge Handbook of Computational Cognitive Modeling, 59-100.
7.5. Referensi tentang AI Berbasis Reinforcement Learning dan Meta-Learning
Referensi ini mendukung implementasi meta-goal adaptation dan pembelajaran hierarkis dalam AGI.
Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd Edition). MIT Press.
 Schmidhuber, J. (1991). "A Possibility for Implementing Curiosity and Boredom in Model-Building Neural Controllers." Proceedings of the International Conference on Simulation of Adaptive Behavior, 222-227.
 Wang, J. X., Kurth-Nelson, Z., Kumaran, D., Tirumala, D., Soyer, H., Leibo, J. Z., ... & Botvinick, M. (2018). "Prefrontal Cortex as a Meta-Reinforcement Learning System." Nature Neuroscience, 21(6), 860-868.
 Finn, C., Abbeel, P., & Levine, S. (2017). "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks." Proceedings of the 34th International Conference on Machine Learning (ICML).
 Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., ... & Hassabis, D. (2017). "Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm." Nature, 550(7676), 354-359.
