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生化通用人工智能——通用人工智能的哲学原理及实例
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Abstract:
近年来，随着脑科学、神经科学、认知科学的发展，人工智能技术取得了一系列成果。但仍然未能实现人类级别通用型的人工智能，有关大脑思维认知结构、意识等问题仍然是人类未解之谜。通过综合宇宙、生命及思维的演化规律，总结出一种通用生化智能模型及其哲学原理和算法结构，并对思维意识各项功能逐一进行举例运算。结果表明该模型及其依据的原理、算法符合智能物种的生物学、物理学、神经科学、认知科学及哲学的基本特征，是一种模拟人类智能的通用人工智能实现模型，对人类的认知、思维、意识的运作模式也有较好的启迪。
In recent years, with the development of brain science, neuroscience and cognitive science, artificial intelligence technology has made a series of achievements. However, it still fails to achieve the human level of universal artificial intelligence, and the cognitive structure and consciousness are still mysteries. This paper integrates the evolutionary laws of the universe, life and thinking, summarizes a model of generated general intelligence and reveals its philosophical principle and algorithm structure, then calculates the functions of thinking and consciousness one by one. The results show that the model and its based principles and algorithms conform to the characteristics of biology, physics, neuroscience, cognitive science and philosophy of intelligent species. It is an implementation model of artificial general intelligence that simulates human intelligence. This paper reveals the characteristics of cognition, thinking and consciousness, which also has a good enlightenment to the operation mode of human cognition, thinking and consciousness.
| [1] | Turing, A.M. (1937) On Computable Numbers, with an Application to the Entscheidungs Problem. Proceedings of the London Mathematical Society, 42, 230-265. https://doi.org/10.1112/plms/s2-42.1.230 |
| [2] | Newell, A., Shaw, J.C. and Simon, H.A. (1957) Empirical Explorations with the Logic Theory Machine: A Case Study in Heuristics. Proceedings of the Western Joint Computer Conference, New York, 26-28 February 1957, 15.
https://doi.org/10.1145/1455567.1455605 |
| [3] | Fan, J.T., Fang, L., Wu, J.M., et al. (2020) From Brain Science to Artificial Intelligence. Engineering, 6, 248-252.
https://doi.org/10.1016/j.eng.2019.11.012 |
| [4] | Savage, N. (2019) Marriage of Mind and Machine. Nature, 571, 15-17. https://doi.org/10.1038/d41586-019-02212-4 |
| [5] | Hoffmann, C.H. (2022) Is AI Intelligent? An Assessment of Artificial Intelligence, 70 Years after Turing. Technology in Society, 68, Article ID: 101893. https://doi.org/10.1016/j.techsoc.2022.101893 |
| [6] | Mira, J.M. (2008) Symbols versus Connections: 50 Years of Artificial Intelligence. Neurocomputing, 71, 671-680.
https://doi.org/10.1016/j.neucom.2007.06.009 |
| [7] | Kasabov, N. (2019) Artificial Intelligence in the Age of Neural Networks and Brain Computing. Academic Press, Pittsburgh. |
| [8] | Zhang, C.M. and Lu, Y. (2021) Study on Artificial Intelligence: The State of the Art and Future Prospects. Journal of Industrial Information Integration, 23, Article ID: 100224. https://doi.org/10.1016/j.jii.2021.100224 |
| [9] | Shafiullah, M., Abido, M.A. and Al-Mohammed, A.H. (2022) Power System Fault Diagnosis. Elsevier, Amsterdam, 69-100. https://doi.org/10.1016/B978-0-323-88429-7.00007-2 |
| [10] | Dwivedi, Y.K., Hughes, L., et al. (2021) Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy. International Journal of Information Management, 57, Article ID: 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 |
| [11] | Garza-Ulloa, J. (2022) Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models. Academic Press, Pittsburgh. https://doi.org/10.1016/B978-0-12-820718-5.00009-X |
| [12] | Kubassova, O., Shaikh, F., et al. (2021) Precision Medicine and Artificial Intelligence. Academic Press, Pittsburgh. |
| [13] | Macpherson, T., Churchland, A., Sejnowski, T., et al. (2021) Natural and Artificial Intelligence: A Brief Introduction to the Interplay between AI and Neuroscience Research. Neural Networks, 144, 603-613.
https://doi.org/10.1016/j.neunet.2021.09.018 |
| [14] | Laberge, Y. (2008) The History of Cognitive Science and Artificial Intelligence. Journal of Chemical Neuroanatomy, 36, 264-265. https://doi.org/10.1016/j.jchemneu.2008.07.006 |
| [15] | Kumpulainen, S. and Terziyan, V. (2022) Artificial General Intelligence vs. Industry 4.0: Do They Need Each Other? Procedia Computer Science, 200, 140-150. https://doi.org/10.1016/j.procs.2022.01.213 |
| [16] | Johnson, M., Albizri, A., Harfouche, A., et al. (2022) Integrating Human Knowledge into Artificial Intelligence for Complex and Ill-Structured Problems: Informed Artificial Intelligence. International Journal of Information Management, 64, Article ID: 102479. https://doi.org/10.1016/j.ijinfomgt.2022.102479 |
| [17] | Dushkin, R.V. and Stepankov, V.Y. (2021) Hybrid Bionic Cognitive Architecture for Artificial General Intelligence Agents. Procedia Computer Science, 190, 226-230. https://doi.org/10.1016/j.procs.2021.06.028 |
| [18] | Lampropoulos, G., Keramopoulos, E. and Diamantaras, K. (2020) Enhancing the Functionality of Augmented Reality Using Deep Learning, Semantic Web and Knowledge Graphs: A Review. Visual Informatics, 4, 32-42.
https://doi.org/10.1016/j.visinf.2020.01.001 |
| [19] | Ruta, M. Scioscia, F., Bilenchi, I., et al. (2022) A Multiplatform Reasoning Engine for the Semantic Web of Everything. Journal of Web Semantics, 73, Article ID: 100709. https://doi.org/10.1016/j.websem.2022.100709 |
| [20] | Wagner, A., Bonduel, M., Pauwels, P. and Ruppel, U. (2020) Representing Construction-Related Geometry in a Semantic Web Context: A Review of Approaches. Automation in Construction, 115, Article ID: 103130.
https://doi.org/10.1016/j.autcon.2020.103130 |
| [21] | Lan, G.J., Liu, T., Wang, X., et al. (2022) A Semantic Web Technology Index. Scientific Reports, 12, Article No. 3672. https://doi.org/10.1038/s41598-022-07615-4 |
| [22] | Shirley, M., Rani, M., Thomas, P., et al. (2020) Transferring Structural Knowledge across Cognitive Maps in Humans and Models. Nature Communications, 11, Article No. 4783. https://doi.org/10.1038/s41467-020-18254-6 |
| [23] | Hendler, J. (2003) Science and the Semantic Web. Science, 299, 520-521. https://doi.org/10.1126/science.1078874 |
| [24] | Zaki, J. and Ochsner, K.N. (2012) The Neuroscience of Empathy: Progress, Pitfalls and Promise. Nature Neuroscience, 15, 675-680. https://doi.org/10.1038/nn.3085 |
| [25] | Panksepp, J. (2011) Behavior. Empathy and the Laws of Affect. Science, 334, 1358-1359.
https://doi.org/10.1126/science.1216480 |
| [26] | Decety, J. and Holvoet, C. (2021) The Emergence of Empathy: A Developmental Neuroscience Perspective. Developmental Review, 62, Article ID: 100999. https://doi.org/10.1016/j.dr.2021.100999 |
| [27] | Abhilash, M. and Santosh, K.M. (2019) A Comprehensive Survey of Recent Developments in Neuronal Communication and Computational Neuroscience. Journal of Industrial Information Integration, 13, 40-54.
https://doi.org/10.1016/j.jii.2018.11.005 |
| [28] | Lewin, R. (1980) Is Your Brain Really Necessary? Science, 210, 1232-1234. https://doi.org/10.1126/science.7434023 |
| [29] | Roy, D.S., Park, Y.-G., Kim, M.E., et al. (2022) Brain-Wide Mapping Reveals that Engrams for a Single Memory Are Distributed across Multiple Brain Regions. Nature Communications, 13, Article No. 1799.
https://doi.org/10.1038/s41467-022-29384-4 |
| [30] | Cohen, D., Nakai, T. and Nishimoto, S. (2022) Brain Networks Are Decoupled from External Stimuli during Internal Cognition. NeuroImage, 256, Article ID: 119230. https://doi.org/10.1016/j.neuroimage.2022.119230 |
| [31] | Ram, V. and Pandey, L. (2008) Subjective Experiences of Space and Time: Self, Sensation, and Phenomenal Time. Nature Precedings. |
| [32] | Richards, B.A., Lillicrap, T.P., Beaudoin, P., et al. (2019) A Deep Learning Framework for Neuroscience. Nature Neuroscience, 22, 1761-1770. https://doi.org/10.1038/s41593-019-0520-2 |
| [33] | Goya-Martinez, M. (2016) In Emotions and Technology, Emotions, Technology, and Design. Academic Press, Pittsburgh. |
| [34] | Windridge, D. and Thill, S. (2018) Representational Fluidity in Embodied (Artificial) Cognition. Biosystems, 172, 9-17. https://doi.org/10.1016/j.biosystems.2018.07.007 |
| [35] | Zhang, M. and Li, J.T. (2021) A Commentary of GPT-3 in MIT Technology Review 2021. Fundamental Research, 1, 831-833. https://doi.org/10.1016/j.fmre.2021.11.011 |
| [36] | Tang, P.C.L. (1999) A Review Essay: Recent Literature on Cognitive Science. The Social Science Journal, 36, 675-686.
https://doi.org/10.1016/S0362-3319(99)00044-0 |
| [37] | Shahriar, S. (2022) GAN Computers Generate Arts? A Survey on Visual Arts, Music, and Literary Text Generation Using Generative Adversarial Network. Displays, 73, Article ID: 102237. https://doi.org/10.1016/j.displa.2022.102237 |
| [38] | Seth, A.K. and Bayne, T. (2022) Theories of Consciousness. Nature Reviews Neuroscience, 23, 439-452.
https://doi.org/10.1038/s41583-022-00587-4 |
