ACP-based social computing and parallel intelligence: Societies 5.0 and beyond

Abstract Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of open-source big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of “social laboratories” in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.

[1]  Long Wang,et al.  Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game , 2012, PloS one.

[2]  Wang Feiyue,et al.  Study on cyber-enabled social movement organizations based on social computing and parallel systems , 2011 .

[3]  Fei-Yue Wang Moving Towards Complex Intelligence? , 2009, IEEE Intell. Syst..

[4]  Liuqing Yang,et al.  Where does AlphaGo go: from church-turing thesis to AlphaGo thesis and beyond , 2016, IEEE/CAA Journal of Automatica Sinica.

[5]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[6]  Wenji Mao,et al.  Cyber-Physical-Social Systems for Command and Control , 2011, IEEE Intelligent Systems.

[7]  Marvin Minsky,et al.  Steps toward Artificial Intelligence , 1995, Proceedings of the IRE.

[8]  Edward H. Glaessgen,et al.  The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles , 2012 .

[9]  Zhi-Dan Zhao,et al.  Empirical analysis of online human dynamics , 2012 .

[10]  Wenji Mao,et al.  Social Computing: From Social Informatics to Social Intelligence , 2007, IEEE Intell. Syst..

[11]  Nan Xiao,et al.  Road pricing design based on game theory and multi-agent consensus , 2014, IEEE/CAA Journal of Automatica Sinica.

[12]  Jure Leskovec,et al.  No country for old members: user lifecycle and linguistic change in online communities , 2013, WWW.

[13]  Tom A. B. Snijders,et al.  Introduction to stochastic actor-based models for network dynamics , 2010, Soc. Networks.

[14]  R. Merton The unanticipated consequences of purposive social action , 1936 .

[15]  Li Li,et al.  Steps toward Parallel Intelligence , 2016 .

[16]  Fei-Yue Wang A Big-Data Perspective on AI: Newton, Merton, and Analytics Intelligence , 2012, IEEE Intell. Syst..

[17]  Haryanti Haryanti,et al.  DNA Profile of Pacific White Shrimp, L. vannamei Infected by Taura Syndrome Virus Using Single Strand Conformation Polymorphism (SSCP) Analysis , 2016 .

[18]  Fei-Yue Wang,et al.  Toward a Paradigm Shift in Social Computing: The ACP Approach , 2007, IEEE Intell. Syst..

[19]  Fei-Yue Wang,et al.  A framework for artificial transportation systems: from computer simulations to computational experiments , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[20]  Robert M. Glorioso,et al.  Engineering Cybernetics , 1975 .

[21]  Lenz Belzner,et al.  A Simulation-Based Architecture for Smart Cyber-Physical Systems , 2016, 2016 IEEE International Conference on Autonomic Computing (ICAC).

[22]  Fei-Yue Wang,et al.  The Emergence of Intelligent Enterprises: From CPS to CPSS , 2010, IEEE Intelligent Systems.

[23]  Yong Yuan,et al.  Social computing and computational societies: The foundation and consequence of smart societies , 2015 .

[24]  Fei-Yue Wang A Letter From the Editor: Intelligent Systems Now , 2009, IEEE Intell. Syst..

[25]  Mohamed Nemiche,et al.  Understanding social behavior evolutions through agent-based modeling , 2012, 2012 International Conference on Multimedia Computing and Systems.

[26]  R. Garrett,et al.  Protest in an Information Society: a review of literature on social movements and new ICTs , 2006 .

[27]  Cameron Marlow,et al.  A 61-million-person experiment in social influence and political mobilization , 2012, Nature.

[28]  J. Earl,et al.  Movement Societies and Digital Protest: Fan Activism and Other Nonpolitical Protest Online* , 2009 .

[29]  G. Nicholas,et al.  The Phenomenon of Man. , 1955 .

[30]  Haibo Ji,et al.  A continuous leader-following consensus control strategy for a class of uncertain multi-agent systems , 2014, IEEE/CAA Journal of Automatica Sinica.

[31]  Nader Moayeri,et al.  Cyber-physical systems: A framework for dynamic traffic light control at road intersections , 2016, 2016 IEEE Wireless Communications and Networking Conference.

[32]  John W Clark,et al.  Linking the web and the street: Internet-based "dotcauses" and the "anti-globalization" movement , 2006 .

[33]  Roberta Ash,et al.  Social Movement Organizations: Growth, Decay and Change , 1966 .

[34]  Thomas Rid Rise of the Machines , 2016 .

[35]  Siu-Ming Yiu,et al.  Security Issues and Challenges for Cyber Physical System , 2010, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing.

[36]  Fei-yue Wang,et al.  Control 5.0: from Newton to Merton in popper's cyber-social-physical spaces , 2016, IEEE/CAA Journal of Automatica Sinica.

[37]  James A. Hendler,et al.  A Study of the Human Flesh Search Engine: Crowd-Powered Expansion of Online Knowledge , 2010, Computer.

[38]  Wang Feiyue,et al.  Parallel system methods for management and control of complex systems , 2004 .

[39]  Wang,et al.  Software-defined systems and knowledge automation: a parallel paradigm shift from newton to merton , 2015 .

[40]  Marc Behl,et al.  Engineering biodegradable micelles of polyethylenimine-based amphiphilic block copolymers for efficient DNA and siRNA delivery. , 2016, Journal of controlled release : official journal of the Controlled Release Society.

[41]  S. Michael Spottswood,et al.  Reengineering Aircraft Structural Life Prediction Using a Digital Twin , 2011 .

[42]  James A. Hendler,et al.  Brokers or Bridges? Exploring Structural Holes in a Crowdsourcing System , 2016, Computer.

[43]  Ralph W. Nicholas,et al.  Social and Political Movements , 1973 .

[44]  Fei-Yue Wang,et al.  Be a Happy and Healthy Dragon! , 2012, IEEE Intell. Syst..