Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems
The strong and functional couplings among ecological, economic, social, and technological processes explain the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Computation |
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| Online Access: | https://www.mdpi.com/2079-3197/10/6/95 |
| _version_ | 1797488566826172416 |
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| author | Alejandro N. Martínez-García |
| author_facet | Alejandro N. Martínez-García |
| author_sort | Alejandro N. Martínez-García |
| collection | DOAJ |
| description | The strong and functional couplings among ecological, economic, social, and technological processes explain the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemic. Among complexification’s features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This, in turn, means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy, and information, and a given time horizon. Given the high-stakes; the need for effective, efficient, diverse solutions; their local and global, and present and future effects; and their unforeseen short-, medium-, and long-term impacts; achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents (SUIAs). The proposed philosophical and technological SUIAs will be heuristic devices for harnessing the strong functional coupling between human, artificial, and nonhuman biological intelligence in a non-zero-sum game to achieve sustainability. |
| first_indexed | 2024-03-10T00:05:06Z |
| format | Article |
| id | doaj.art-38b20096a27148ec8a7aa0825ea77265 |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-10T00:05:06Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-38b20096a27148ec8a7aa0825ea772652023-11-23T16:09:40ZengMDPI AGComputation2079-31972022-06-011069510.3390/computation10060095Artificial Intelligence for Sustainable Complex Socio-Technical-Economic EcosystemsAlejandro N. Martínez-García0Tecnológico Nacional de México-Valle de Morelia, 58100 Morelia, Michoacán de Ocampo, MexicoThe strong and functional couplings among ecological, economic, social, and technological processes explain the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemic. Among complexification’s features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This, in turn, means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy, and information, and a given time horizon. Given the high-stakes; the need for effective, efficient, diverse solutions; their local and global, and present and future effects; and their unforeseen short-, medium-, and long-term impacts; achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents (SUIAs). The proposed philosophical and technological SUIAs will be heuristic devices for harnessing the strong functional coupling between human, artificial, and nonhuman biological intelligence in a non-zero-sum game to achieve sustainability.https://www.mdpi.com/2079-3197/10/6/95artificial and biological intelligencecomplex coevolutionary systems engineeringsustainabilitymulti-objective optimizationsustainable universal intelligent agents |
| spellingShingle | Alejandro N. Martínez-García Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems Computation artificial and biological intelligence complex coevolutionary systems engineering sustainability multi-objective optimization sustainable universal intelligent agents |
| title | Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems |
| title_full | Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems |
| title_fullStr | Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems |
| title_full_unstemmed | Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems |
| title_short | Artificial Intelligence for Sustainable Complex Socio-Technical-Economic Ecosystems |
| title_sort | artificial intelligence for sustainable complex socio technical economic ecosystems |
| topic | artificial and biological intelligence complex coevolutionary systems engineering sustainability multi-objective optimization sustainable universal intelligent agents |
| url | https://www.mdpi.com/2079-3197/10/6/95 |
| work_keys_str_mv | AT alejandronmartinezgarcia artificialintelligenceforsustainablecomplexsociotechnicaleconomicecosystems |