1.中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190
2.中国科学院自动化研究所复杂系统管理与控制国家重点实验室,北京 100190
3.澳门科技大学创新工程学院,澳门 999078
[ "李娟娟(1986- ),女,博士,中国科学院自动化研究所多模态人工智能系统全国重点实验室副研究员,主要研究方向为区块链智能、Web 3.0与平行管理。" ]
[ "管桑田(1997- ),男,中国科学院自动化研究所多模态人工智能系统全国重点实验室研究助理,主要研究方向为去中心化经济、Web 3.0与平行管理。" ]
[ "秦蕊(1983- ),女,博士,中国科学院自动化研究所多模态人工智能系统全国重点实验室副研究员,主要研究方向为区块链智能、DAO与平行管理。" ]
[ "侯家琛(1986- ),男,澳门科技大学创新工程学院博士生,主要研究方向为DAO、智能交通以及分布式管理。" ]
[ "王飞跃(1961- ),男,博士,中国科学院自动化研究所研究员,复杂系统管理与控制国家重点实验室主任,中国科学院大学中国经济与社会安全研究中心主任,澳门科技大学特聘教授,主要研究方向为平行系统的方法与应用、社会计算、平行智能、知识自动化。" ]
收稿:2024-02-03,
修回:2024-03-01,
纸质出版:2024-03-15
移动端阅览
李娟娟, 管桑田, 秦蕊, 等. 智能区块链与区块链智能:构筑DePIN的基础设施智能[J]. 智能科学与技术学报, 2024,6(1):5-16.
LI Juanjuan, GUAN Sangtian, QIN Rui, et al. Intelligent blockchains and blockchain intelligence: the infrastructure intelligence for DePIN[J]. Chinese Journal of Intelligent Science and Technology, 2024, 6(1): 5-16.
李娟娟, 管桑田, 秦蕊, 等. 智能区块链与区块链智能:构筑DePIN的基础设施智能[J]. 智能科学与技术学报, 2024,6(1):5-16. DOI: 10.11959/j.issn.2096-6652.202403.
LI Juanjuan, GUAN Sangtian, QIN Rui, et al. Intelligent blockchains and blockchain intelligence: the infrastructure intelligence for DePIN[J]. Chinese Journal of Intelligent Science and Technology, 2024, 6(1): 5-16. DOI: 10.11959/j.issn.2096-6652.202403.
去中心化物理基础设施网络是未来数字社会不可或缺的基石,它将传统依赖于集中式控制和管理的物理设施转变为由社区驱动且自主治理的新型基础设施网络,而区块链与人工智能(artificial intelligence,AI)技术的深度融合在其中起到了关键的赋能作用。为此,首先强调有机结合“AI赋能区块链”与“区块链赋能AI”,形成协同增效的双向闭环回路,以构建真正意义上的智能区块链,从而实现区块链智能新范式。其次,提出智能区块链的新型技术架构:一方面,将智能性内嵌至传统区块链架构的每一层,以培育从基础智能到基础设施智能再到应用智能的区块链智能生态;另一方面,为实际智能区块链构建与之对应的人工的智能区块链,并通过二者的虚实反馈与平行执行,形成从静态规则导向到动态适应演进的区块链智能生态。然后,从智慧合约、去中心化身份、知识管理、自主治理等角度辨析区块链智能的核心智能属性。最后,概述区块链智能的典型应用场景及面临的关键挑战。积极推进智能区块链与区块链智能技术的研究与发展,有助于构筑未来数字时代的核心基础设施。
Decentralized physical infrastructure networks (DePIN) were an indispensable cornerstone for the upcoming digital society
transforming traditional infrastructure reliant on centralized control and management into a new type of infrastructure network driven by communities and autonomous governance. The deep integration of blockchain and artificial intelligence (AI) technologies played a key role in enabling this transformation. To this end
this paper first emphasized the organic combination of "AI for blockchain (AI4B)" and "blockchain for AI (B4AI)"
forming a synergistic
bidirectional closed-loop circuit to construct the truly intelligent blockchains
thereby realizing a new paradigm of blockchain intelligence. Secondly
it proposed a novel technological architecture for intelligent blockchains: on one hand
embedding intelligence into every layer of traditional blockchain architecture to cultivate the blockchain intelligence ecosystem ranging from foundational intelligence to infrastructure intelligence and then to application intelligence; on the other hand
corresponding to the actual intelligent blockchain construction
artificial intelligent blockchain were built
and through their virtual-real feedback and parallel execution
the blockchain intelligence ecosystem evolved from static rule orientation to dynamic adaptive evolution. Then
it analyzed the core intelligent attributes of blockchain intelligence from the perspectives of intelligent contracts
decentralized identity
knowledge management
and autonomous governance. Lastly
it outlined the typical application scenarios of blockchain intelligence and the key challenges faced. This paper aims to actively promote the research and development of intelligent blockchains and blockchain intelligence technologies
laying the foundation for building the core infrastructure of the future digital age.
LI J J, YUAN Y, WANG F Y. A novel GSP auction mechanism for ranking Bitcoin transactions in blockchain mining[J]. Decision Support Systems, 2019, 124: 113094.
LI J J, NI X C, YUAN Y, et al. A novel GSP auction mechanism for dynamic confirmation games on Bitcoin transactions[J]. IEEE Transactions on Services Computing, 2022, 15(3): 1436-1447.
QIN R, DING W W, LI J J, et al. Web3-based decentralized autonomous organizations and operations: architectures, models, and mechanisms[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53: 2073-2082.
李娟娟, 秦蕊, 丁文文, 等. 基于Web3的去中心化自治组织与运营新框架[J]. 自动化学报, 2023, 49(5): 985-998.
LI J J, QIN R, DING W W, et al. A new framework for Web3-powered decentralized autonomous organizations and operations[J]. Acta Automatica Sinica, 2023, 49(5): 985-998.
LI J J, LIANG X L, QIN R, et al. From DAO to TAO: finding the essence of decentralization[C]//IEEE International Conference on Systems, Man, and Cybernetics. [S.l.:s.n.], 2023: 4283-4288.
LI J J, WANG F Y. The TAO of blockchain intelligence for intelligent Web3.0[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(12): 2183-2186.
WANG F Y. The generalized Gödel theorem and blockchain intelligence: in math we can't trust[C]//The Conference of Blockchain and Mathematics. [S.l.:s.n.], 2018.
MARWALA T, XING B. Blockchain and artificial intelligence[EB]. arXiv preprint, 2019, arXiv: 1802.04451.
HUSSAIN A A, AL-TURJMAN F. Artificial intelligence and blockchain: a review[J]. Transactions on Emerging Telecommunications Technologies, 2021, 32(9): e4268.
LIU C H, LIN Q X, WEN S L. Blockchain-enabled data collection and sharing for industrial IoT with deep reinforcement learning[J]. IEEE Transactions on Industrial Informatics, 2019, 15(6): 3516-3526.
WANG G, LI J J, WANG X, et al. Blockchain-based crypto management for reliable real-time decision-making[J]. IEEE Transactions on Computational Social Systems, 2023, 10(6): 3333-3342.
KRITTANAWONG C, ROGERS A J, AYDAR M, et al. Integrating blockchain technology with artificial intelligence for cardiovascular medicine[J]. Nature Reviews Cardiology, 2020, 17(1): 1-3.
GUO S Y, ZHANG F, GUO S, et al. Blockchain-assisted privacy-preserving data computing architecture for Web3[J]. IEEE Communications Magazine, 2023, 61(8): 28-34.
LIN Y J, GAO Z P, DU H Y, et al. A unified blockchain-semantic framework for wireless edge intelligence enabled Web 3.0[J]. IEEE Wireless Communications, 2023, doi: 10.1109/MWC.018.2200568.
AGARWAL A, DAHLEH M, SARKAR T. A marketplace for data: an algorithmic solution[C]//Proceedings of the 2019 ACM Conference on Economics and Computation, [S.l.:s.n.], 2019: 701-726.
LU Y L, HUANG X H, ZHANG K, et al. Blockchain and federated learning for 5G beyond[J]. IEEE Network, 2021, 35(1): 219-225.
LIU Y, WANG H S, PENG M G, et al. An incentive mechanism for privacy-preserving crowdsensing via deep reinforcement learning[J]. IEEE Internet of Things Journal, 2021, 8(10): 8616-8631.
DU H Y, WANG J C, NIYATO D, et al. AI-generated incentive mechanism and full-duplex semantic communications for information sharing[J]. IEEE Journal on Selected Areas in Communications, 2023, 41(9): 2981-2997.
HE D J, WU R, LI X J, et al. Detection of vulnerabilities of blockchain smart contracts[J]. IEEE Internet of Things Journal, 2023, 10(14): 12178-12185.
ZHUANG Y, LIU Z G, QIAN P, et al. Smart contract vulnerability detection using graph neural network[C]//Proceedings of the 29th International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2020: 3283-3290.
GAO Z P. When deep learning meets smart contracts[C]//Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering. New York: ACM, 2020: 1400-1402.
TANG X, LAN X Q, LI L X, et al. Incentivizing proof-of-stake blockchain for secured data collection in UAV-assisted IoT: a multi-agent reinforcement learning approach[J]. IEEE Journal on Selected Areas in Communications, 2022, 40(12): 3470-3484.
BRAVO-MARQUEZ F, REEVES S, UGARTE M. Proof-of-learning: a blockchain consensus mechanism based on machine learning competitions[C]//Proceedings of the 2019 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPCON). Piscataway: IEEE Press, 2019: 119-124.
KOSTER R, BALAGUER J, TACCHETTI A, et al. Human-centred mechanism design with Democratic AI[J]. Nature Human Behaviour, 2022, 6(10): 1398-1407.
WANG X F, REN X X, QIU C, et al. Integrating edge intelligence and blockchain: what, why, and how[J]. IEEE Communications Surveys & Tutorials, 2022, 24(4): 2193-2229.
ZHAO J, ZHU X H, WANG J Z, et al. Efficient client contribution evaluation for horizontal federated learning[C]//Proceedings of the ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Piscataway: IEEE Press, 2021: 3060-3064.
WU J J, LIU J L, CHEN W L, et al. Detecting mixing services via mining Bitcoin transaction network with hybrid motifs[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 52(4): 2237-2249.
CHEN L, PENG J Y, LIU Y, et al. Phishing scams detection in ethereum transaction network[J]. ACM Transactions on Internet Technology, 2020, 21(1): 1-16.
ZHENG P L, ZHENG Z B, CHEN L. Selecting reliable blockchain peers via hybrid blockchain reliability prediction[J]. IET Software, 2023, 17(4): 362-377.
LIU Y M, YU F R, LI X, et al. Blockchain and machine learning for communications and networking systems[J]. IEEE Communications Surveys & Tutorials, 2020, 22(2): 1392-1431.
WU J J, YUAN Q, LIN D, et al. Who are the phishers? phishing scam detection on ethereum via network embedding[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 52(2): 1156-1166.
GUO F X, YU F R, ZHANG H L, et al. Adaptive resource allocation in future wireless networks with blockchain and mobile edge computing[J]. IEEE Transactions on Wireless Communications, 2020, 19(3): 1689-1703.
BURGGRAF T. Beyond risk parity–a machine learning-based hierarchical risk parity approach on cryptocurrencies[J]. Finance Research Letters, 2021, 38: 101523.
ZHOU J J, HU C K, CHI J L, et al. Behavior-aware account de-anonymization on ethereum interaction graph[J]. IEEE Transactions on Information Forensics and Security, 2022, 17: 3433-3448.
林知微, 张嵩川, 王成吉, 等. 区块链技术综述:在下一代智能制造中的应用[J]. 智能科学与技术学报, 2023, 5(2): 200-211.
LIN Z W, ZHANG S C, WANG C J, et al. A survey on application of block chain in next generation intelligent manufacturing[J]. Chinese Journal of Intelligent Science and Technology, 2023, 5(2): 200-211.
MAXMEN A. AI researchers embrace Bitcoin technology to share medical data[J]. Nature, 2018, 555(7696): 293-294.
ABADI M, CHU A, GOODFELLOW I, et al. Deep learning with differential privacy[C]//Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. New York: ACM, 2016: 308-318.
DRAKATOS P, DEMETRIOU E, KOUMOU S, et al. Triastore: a web 3.0 blockchain datastore for massive IoT workloads[C]//Proceedings of the 2021 22nd IEEE International Conference on Mobile Data Management (MDM). Piscataway: IEEE Press, 2021: 187-192.
SHEN M, TANG X Y, ZHU L H, et al. Privacy-preserving support vector machine training over blockchain-based encrypted IoT data in smart cities[J]. IEEE Internet of Things Journal, 2019, 6(5): 7702-7712.
LI J J, LI J Q, WANG X, et al. Multi-blockchain based data trading markets with novel pricing mechanisms[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(12): 2222-2232.
李娟娟, 王戈, 王晓, 等. 加密管理:一种基于区块链的新型组织管理模式[J]. 智能科学与技术学报, 2022, 4(2): 145-156.
LI J J, WANG G, WANG X, et al. Crypto management: a novel organizational management model based on blockchain[J]. Chinese Journal of Intelligent Science and Technology, 2022, 4(2): 145-156.
FAN S Z, ZHANG H B, ZENG Y C, et al. Hybrid blockchain-based resource trading system for federated learning in edge computing[J]. IEEE Internet of Things Journal, 2021, 8(4): 2252-2264.
DU Y, WANG Z, LI J, et al. Blockchain-aided edge computing market: smart contract and consensus mechanisms[J]. IEEE Transactions on Mobile Computing, 2023, 22(6): 3193-3208.
OUYANG L W, YUAN Y, WANG F Y. Learning markets: an AI collaboration framework based on blockchain and smart contracts[J]. IEEE Internet of Things Journal, 2022, 9(16): 14273-14286.
REN Y Z, XIE R C, YU F R, et al. NFT-based intelligence networking for connected and autonomous vehicles: a quantum reinforcement learning approach[J]. IEEE Network, 2022, 36(6): 116-124.
TENG S Y, HU X M, DENG P, et al. Motion planning for autonomous driving: the state of the art and future perspectives[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(6): 3692-3711.
MONTES G A, GOERTZEL B. Distributed, decentralized, and democratized artificial intelligence[J]. Technological Forecasting and Social Change, 2019, 141: 354-358.
JOGUNOLA O, ADEBISI B, IKPEHAI A, et al. Consensus algorithms and deep reinforcement learning in energy market: a review[J]. IEEE Internet of Things Journal, 2021, 8(6): 4211-4227.
CUI L Z, SU X X, MING Z X, et al. CREAT: blockchain-assisted compression algorithm of federated learning for content caching in edge computing[J]. IEEE Internet of Things Journal, 2022, 9(16): 14151-14161.
KANG J W, LI X D, NIE J T, et al. Communication-efficient and cross-chain empowered federated learning for artificial intelligence of things[J]. IEEE Transactions on Network Science and Engineering, 2022, 9(5): 2966-2977.
KANG J W, XIONG Z H, NIYATO D, et al. Incentive mechanism for reliable federated learning: a joint optimization approach to combining reputation and contract theory[J]. IEEE Internet of Things Journal, 2019, 6(6): 10700-10714.
FU Y C, LI C L, YU F R, LUAN T H, ZHAO P C. An incentive mechanism of incorporating supervision game for federated learning in autonomous driving[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(12): 14800-14812.
FU Y C, LI C L, YU F R, et al. An incentive mechanism of incorporating supervision game for federated learning in autonomous driving[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(12): 14800-14812.
JIANG C, XU C, ZHANG Y. PFLM: privacy-preserving federated learning with membership proof[J]. Information Sciences, 2021, 576: 288-311.
WANG L L, ZHAO X Q, LU Z K, et al. Enhancing privacy preservation and trustworthiness for decentralized federated learning[J]. Information Sciences, 2023, 628: 449-468.
SAI S, HASSIJA V, CHAMOLA V, et al. Federated learning and NFT-based privacy-preserving medical-data-sharing scheme for intelligent diagnosis in smart healthcare[J]. IEEE Internet of Things Journal, 2024, 11(4): 5568-5577.
LANG P, TIAN D X, DUAN X T, et al. Blockchain-based cooperative computation offloading and secure handover in vehicular edge computing networks[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(7): 3839-3853.
ZHANG W S, SUN G, XU L, et al. A trustworthy safety inspection framework using performance-security balanced blockchain[J]. IEEE Internet of Things Journal, 2022, 9(11): 8178-8190.
ZHU Z Q, WANG X, ZHAO Y, et al. Crowdsensing intelligence by decentralized autonomous vehicles organizations and operations[J]. IEEE Transactions on Intelligent Vehicles, 2022, 7(4): 804-808.
LI T, FANG Y Z, LU Y, et al. SmartVM: a smart contract virtual machine for fast on-chain DNN computations[J]. IEEE Transactions on Parallel and Distributed Systems, 2022, 33(12): 4100-4116.
SAMI H, MIZOUNI R, OTROK H, et al. LearnChain: transparent and cooperative reinforcement learning on blockchain[J]. Future Generation Computer Systems, 2024, 150: 255-271.
KAREEM A, AHMED E, MOHAMED M. Decentralizing construction AI applications using blockchain technology[J]. Expert Systems With Applications, 2022, 194: 116548.
CASTELLÓFERRER E, ARAI K, BHATIA R, et al. The blockchain: a new framework for robotic swarm systems[C]// Proceedings of the Future Technologies Conference 2018. [S.l.:s.n.], 2019: 1037-1058.
XUE X, LI G D, ZHOU D Y, et al. Research roadmap of service ecosystems: a crowd intelligence perspective[J]. International Journal of Crowd Science, 2022, 6(4): 195-222.
MA Z F, WANG X C, JAIN D K, et al. A blockchain-based trusted data management scheme in edge computing[J]. IEEE Transactions on Industrial Informatics, 2020, 16(3): 2013-2021.
WANG F Y, QIN R, WANG X, et al. MetaSocieties in metaverse: MetaEconomics and MetaManagement for MetaEnterprises and MetaCities[J]. IEEE Transactions on Computational Social Systems, 2022, 9(1): 2-7.
WANG X X, CHENG X, LU J W, et al. Metaverses-based parallel oil fields in CPSS: a framework and methodology[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2138-2147.
YANG D S, LI Q, ZHU F H, et al. Parallel emergency management of incidents by integrating OODA and PREA loops: the C2 mechanism and modes[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2160-2172.
XUE X, CHEN F Y, ZHOU D Y, et al. Computational experiments for complex social systems—Part I: the customization of computational model[J]. IEEE Transactions on Computational Social Systems, 2022, 9(5): 1330-1344.
XUE X, SHEN Y F, YU X N, et al. Computational experiments: a new analysis method for cyber-physical-social systems[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(2): 813-826.
CHEN J C, ZHANG Y K, TENG S Y, et al. ACP-based energy-efficient schemes for sustainable intelligent transportation systems[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(5): 3224-3227.
WANG J C, TANG Y, HARE R, et al. Parallel intelligent education with ChatGPT[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(1): 12-18.
QIN R, YUAN Y, WANG F Y. Blockchain-based knowledge automation for CPSS-oriented parallel management[J]. IEEE Transactions on Computational Social Systems, 2020, 7(5): 1180-1188.
WANG J G, TIAN Y L, WANG Y T, et al. A framework and operational procedures for metaverses-based industrial foundation models[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2037-2046.
YANG J, LI S M, WANG X X, et al. DeFACT in ManuVerse for parallel manufacturing: foundation models and parallel workers in smart factories[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2188-2199.
TIAN Y L, LI X, ZHANG H, et al. VistaGPT: generative parallel transformers for vehicles with intelligent systems for transport automation[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(9): 4198-4207.
LI X, TIAN Y L, YE P J, et al. A novel scenarios engineering methodology for foundation models in metaverse[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2148-2159.
HAN J P, YANG M Z, CHEN X G, et al. ParaDefender: a scenario-driven parallel system for defending metaverses[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2118-2127.
LI J J, QIN R, WANG F Y. The future of management: DAO to smart organizations and intelligent operations[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(6): 3389-3399.
LI J J, QIN R, OLAVERRI-MONREAL C, et al. Logistics 5.0: from intelligent networks to sustainable ecosystems[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(7): 3771-3774.
QIN R, LI J J, LIANG X L, et al. Management-oriented operating systems: harnessing the power of DAOs and foundation models[C]//Proceedings of the 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Piscataway: IEEE Press, 2023: 3180-3185.
LI J J, YUAN Y, WANG F Y. Analyzing Bitcoin transaction fees using a queueing game model[J]. Electronic Commerce Research, 2022, 22(1): 135-155.
OUYANG L W, ZHANG W W, WANG F Y. Intelligent contracts: making smart contracts smart for blockchain intelligence[J]. Computers and Electrical Engineering, 2022, 104: 108421.
WANG Y T, WANG X, WANG X X, et al. The ChatGPT after: building knowledge factories for knowledge workers with knowledge automation[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(11): 2041-2044.
DING W W, LIANG X L, HOU J C, et al. A novel approach for predictable governance of decentralized autonomous organizations based on parallel intelligence[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(5): 3092-3103.
WANG G, QIN R, LI J J, et al. A novel DAO-based parallel enterprise management framework in Web3 era[J]. IEEE Transactions on Computational Social Systems, 2024, 11(1): 839-848.
王飞跃. 平行管理: 复杂性管理智能的生态科技与智慧管理之DAO[J]. 自动化学报, 2022, 48(11): 2655-2669.
WANG F Y. Parallel management: the DAO to smart ecological technology for complexity management intelligence[J]. Acta Automatica Sinica, 2022, 48(11): 2655-2669.
DING W W, LI J J, QIN R, et al. A new architecture and mechanism for decentralized science MetaMarkets[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(9): 5321-5330.
WANG F Y. Parallel economics: a new supply-demand philosophy via parallel organizations and parallel management[J]. IEEE Transactions on Computational Social Systems, 2020, 7(4): 840-848.
LIN Y L, NA X X, WANG D, et al. Mobility 5.0: smart logistics and transportation services in cyber-physical-social systems[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(6): 3527-3532.
CHEN Y Y, ZHANG H, WANG F Y. Society-centered and DAO-powered sustainability in transportation 5.0: an intelligent vehicles perspective[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(4): 2635-2638.
WANG X X, YANG J, WANG Y T, et al. Steps toward industry 5.0: building "6S" parallel industries with cyber-physical-social intelligence[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(8): 1692-1703.
LI J J, QIN R, GUAN S T, et al. Digital CEOs in digital enterprises: automating, augmenting, and parallel in metaverse/CPSS/TAOs[J]. IEEE/CAA Journal of Automatica Sinica, 2024, 11(4): 820-823.
WANG F Y, MIAO Q H, LI L X, et al. When does sora show: the beginning of TAO to imaginative intelligence and scenarios engineering[J]. IEEE/CAA Journal of Automatica Sinica, 2024, 11(4): 809-815.
QIN R, WANG F Y, ZHENG X L, et al. Sora for computational social systems: From counterfactual experiments to artificiofactual experiments[J]. IEEE Transactions on Computational Social Systems, 2024, 11(2): 1529-1548.
倪清桦, 郭超, 王飞跃. 平行戏剧: 新时代戏剧的人机协同创作与智能管理[J]. 智能科学与技术学报, 2023, 5(4): 436-445.
NI Q H, GUO C, WANG F Y. Parallel theaters: human-machine collaborative creation and intelligent management for theatrical art[J]. Chinese Journal of Intelligent Science and Technology, 2023, 5(4): 436-445.
0
浏览量
529
下载量
5
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621
