Atoms themselves have no thoughts and cannot be thinking. Why does the human body, which is composed of atoms, have consciousness? The widely used concepts of information and intelligence in today’s science, which are related to this, do not yet have appropriate general definitions. Answering these interesting questions is a crucial issue for technological development in the historical context of human society entering the era of intelligence. The key lies in how to fully utilize the existing fundamental theories subtly related to information science. Here we attempt to give the definition of general information and general intelligence from the perspective of generalized natural computing, based on the least action principle, Hamilton-Jacobi equation, dynamic programming, reinforcement learning, and point out the relationship between the two. The least action principle for describing conservative systems can be seen as an intelligent manifestation of natural matter, and its equivalent form, the Hamilton-Jacobi equation, can be extended to describe quantum phenomena and is a special case of continuous dynamic programming equations. Dynamic programming is an efficient optimization method under deterministic models, while reinforcement learning, as a manifestation of biological intelligence, is its model-free version. The statement that reinforcement learning is the most promising machine learning method has a profound physical foundation. General information is defined as the degree to which a certain environmental element determines the behavior of the subject. General intelligence is defined as the automatic optimization ability of the action or value function of a system with a certain degree of conservatism. Intelligence is a basic property of material systems, rather than an emergent property that only complex systems possess. Consciousness is an advanced intelligent phenomenon, a reconstruction of quasi conservative systems based on complex systems.
| Published in | Applied and Computational Mathematics (Volume 13, Issue 5) |
| DOI | 10.11648/j.acm.20241305.17 |
| Page(s) | 187-193 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Consciousness, Intelligence, Information, Conservative Systems, Reinforcement Learning, Dynamic Programming
| [1] | Wiese, W. Toward a Mature Science of Consciousness. Front. Psychol. 2018, 9, 1-15. |
| [2] | Sarasso, S., Casali, A. G., Casarotto, S., et al. Consciousness and complexity: a consilience of evidence. Neurosci. Consci. 2021, 7, 1-24. |
| [3] | Veit, W. Complexity and the Evolution of Consciousness. Biol. Theory. 2023, 18, 175-190. |
| [4] | Arsiwalla, X. D., Solé, R., Moulin-Frier, C., et al. The Morphospace of Consciousness: Three Kinds of Complexity for Minds and Machines. NeuroSci. 2023, 4, 79-102. |
| [5] | Sternberg, R. J. A Theory of Adaptive Intelligence and Its Relation to General Intelligence. J. Intell. 2019, 7, 23-39. |
| [6] | Minqi, J., Tim, R. and Edward G. General intelligence requires rethinking exploration. R. Soc. Open Sci.2023, 10, 230539. |
| [7] | Kanaya, T., Magine, A. How Can the Current State of AI Guide Future Conversations of General Intelligence? J. Intell. 2024, 12, 36-43. |
| [8] | Chaitin, G. J. An Invitation to Algorithmic Information Theory. Arxiv Print. 1996. |
| [9] | Dohn, N. B., Kafai, Y., Mørch, A. et al. Survey: Artificial Intelligence, Computational Thinking and Learning. Künstl. Intell. 2022, 36, 5-16. |
| [10] | Rosenbloom, P. S. Computing and Computation. Comput. J. 2012, 55, 820-824. |
| [11] | Castro, L. N. Fundamentals of natural computing: an overview, Phys. Life Rev. 2007, 4, 1-36. |
| [12] | Gondran, M. The Principle of Least Action as interpreted by Nature and by the Observer, Arxiv Preprint. 2015. |
| [13] | Houchmandzadeh, B. The Hamilton-Jacobi Equation: an intuitive approach. Arxiv Preprint. 2019. |
| [14] | Field, J. H. Derivation of the Schrödinger equation from the Hamilton-Jacobi equation in Feynman’s path integral formulation of quantum mechanics. Eur. J. Phys. 2011, 32, 63-87. |
| [15] | Liberzon, D. Calculus of Variations and Optimal Control Theory: a concise introduction. Princeton: Princeton University Press; 2012. |
| [16] | Bertsekas, D. P. Reinforcement Learning and Optimal Control. Beijing: Tsinghua University Press; 2019. |
| [17] | Legg, S., Hutter, M. A colletion of definition of intelligence. Front. Artif. Intell. appl. 2007, 157, 17-24. |
| [18] | Dehaene, S., Lau, H., Kouider, S. What is consciousness, and could machines have it. Science. 2017, 358, 486-492. |
| [19] | Mashour, G. A., Roelfsema, P., Changeux, J. P., Dehaene, S. Conscious processing and the global neuronal workspace hypothesis. Neuron. 2020, 105, 776-798. |
| [20] | Melloni, L., Mudrik, L., Pitts, M., Koch, C. Making the hard problem of consciousness easier. Science. 2021, 372, 911-912. |
| [21] | Butlin, P., Long, R. Elmoznino, E., et al. Consciousness in artificial intelligence: insights from the science of consciousness. Arxiv Preprint. 2023. |
| [22] | Tononi, G., Boly, M., Massimini, M., Koch, C. Integrated information theory: from consciousness to its physical substrate, Nat. Rev. Neurosci. 2016, 17, 450-461. |
| [23] | Levine, J. Purple Haze: The Puzzle of Consciousness. Oxford: Oxford University Press; 2001. |
| [24] | Lou, H. C., Changeux, J. P., Rosenstand, A. Towards a cognitive neuroscience of self-awareness. Neurosci. Biobehav. Rev. 2017, 83, 765-773. |
| [25] | Lou, H. C., Thomsen, K. R., Changeux, J.P. The Molecular Organization of Self-awareness: Paralimbic Dopamine-GABA Interaction. Front. Syst. Neurosci. 2020, 14, 1-5. |
| [26] | Rosenstand, A. F., Thomsen, K. R., Lou, H. C. Conscious self-monitoring: from molecule to culture. Culture and Brain. 2022, 10, 1-9. |
| [27] | Enders, P. Huygens’ principle as universal model of propagation. Lat. Am. J. Phys. Educ. 2009, 3, 19-32. |
| [28] | Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 1948, 27, 379-423. |
| [29] | Witten, E. A mini-introduction to information theory. Arxiv Preprint. 2018. |
| [30] | Madden, A. D. A definition of information, Aslib Proceedings. 2000, 52, 343-349. |
| [31] | Schaeffer, R., Miranda, B., Koyejo, S. Are Emergent Abilities of Large Language Models a Mirage. Arxiv Preprint. 2023. |
| [32] | Mastropietro, A., Pasculli, G. and Bajorath, J. Learning characteristics of graph neural networks predicting protein-ligand affinities. Nat. Mach. Intell. 2023, 5, 1427- 1436. |
| [33] | Zhang, W., Gao, B., Tang, J., et al. Neuro-inspired computing chips. Nature Electronics. 2020, 3, 371-382. |
| [34] | Ambrogio, S., Narayanan, P., Okazaki, A., et al. An analog-AI chip for energy-efficient speech recognition and transcription. Nature. 2023, 620, 768-775. |
| [35] | Chen, Y., Nazhamaiti, M., Xu, H., et al. All-analog photoelectronic chip for high-speed vision tasks. Nature. 2023, 623, 48-57. |
APA Style
Zhang, L. (2024). General Definitions of Information, Intelligence, and Consciousness from the Perspective of Generalized Natural Computing. Applied and Computational Mathematics, 13(5), 187-193. https://doi.org/10.11648/j.acm.20241305.17
ACS Style
Zhang, L. General Definitions of Information, Intelligence, and Consciousness from the Perspective of Generalized Natural Computing. Appl. Comput. Math. 2024, 13(5), 187-193. doi: 10.11648/j.acm.20241305.17
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.acm.20241305.17,
author = {Linsen Zhang},
title = {General Definitions of Information, Intelligence, and Consciousness from the Perspective of Generalized Natural Computing
},
journal = {Applied and Computational Mathematics},
volume = {13},
number = {5},
pages = {187-193},
doi = {10.11648/j.acm.20241305.17},
url = {https://doi.org/10.11648/j.acm.20241305.17},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20241305.17},
abstract = {Atoms themselves have no thoughts and cannot be thinking. Why does the human body, which is composed of atoms, have consciousness? The widely used concepts of information and intelligence in today’s science, which are related to this, do not yet have appropriate general definitions. Answering these interesting questions is a crucial issue for technological development in the historical context of human society entering the era of intelligence. The key lies in how to fully utilize the existing fundamental theories subtly related to information science. Here we attempt to give the definition of general information and general intelligence from the perspective of generalized natural computing, based on the least action principle, Hamilton-Jacobi equation, dynamic programming, reinforcement learning, and point out the relationship between the two. The least action principle for describing conservative systems can be seen as an intelligent manifestation of natural matter, and its equivalent form, the Hamilton-Jacobi equation, can be extended to describe quantum phenomena and is a special case of continuous dynamic programming equations. Dynamic programming is an efficient optimization method under deterministic models, while reinforcement learning, as a manifestation of biological intelligence, is its model-free version. The statement that reinforcement learning is the most promising machine learning method has a profound physical foundation. General information is defined as the degree to which a certain environmental element determines the behavior of the subject. General intelligence is defined as the automatic optimization ability of the action or value function of a system with a certain degree of conservatism. Intelligence is a basic property of material systems, rather than an emergent property that only complex systems possess. Consciousness is an advanced intelligent phenomenon, a reconstruction of quasi conservative systems based on complex systems.
},
year = {2024}
}
TY - JOUR T1 - General Definitions of Information, Intelligence, and Consciousness from the Perspective of Generalized Natural Computing AU - Linsen Zhang Y1 - 2024/10/10 PY - 2024 N1 - https://doi.org/10.11648/j.acm.20241305.17 DO - 10.11648/j.acm.20241305.17 T2 - Applied and Computational Mathematics JF - Applied and Computational Mathematics JO - Applied and Computational Mathematics SP - 187 EP - 193 PB - Science Publishing Group SN - 2328-5613 UR - https://doi.org/10.11648/j.acm.20241305.17 AB - Atoms themselves have no thoughts and cannot be thinking. Why does the human body, which is composed of atoms, have consciousness? The widely used concepts of information and intelligence in today’s science, which are related to this, do not yet have appropriate general definitions. Answering these interesting questions is a crucial issue for technological development in the historical context of human society entering the era of intelligence. The key lies in how to fully utilize the existing fundamental theories subtly related to information science. Here we attempt to give the definition of general information and general intelligence from the perspective of generalized natural computing, based on the least action principle, Hamilton-Jacobi equation, dynamic programming, reinforcement learning, and point out the relationship between the two. The least action principle for describing conservative systems can be seen as an intelligent manifestation of natural matter, and its equivalent form, the Hamilton-Jacobi equation, can be extended to describe quantum phenomena and is a special case of continuous dynamic programming equations. Dynamic programming is an efficient optimization method under deterministic models, while reinforcement learning, as a manifestation of biological intelligence, is its model-free version. The statement that reinforcement learning is the most promising machine learning method has a profound physical foundation. General information is defined as the degree to which a certain environmental element determines the behavior of the subject. General intelligence is defined as the automatic optimization ability of the action or value function of a system with a certain degree of conservatism. Intelligence is a basic property of material systems, rather than an emergent property that only complex systems possess. Consciousness is an advanced intelligent phenomenon, a reconstruction of quasi conservative systems based on complex systems. VL - 13 IS - 5 ER -
Research Center for Applied Mathematics and Interdisciplinary Sciences, School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan, China
