IJCAI 2013 Tutorial

Human-Machine-Nature Symbiosis

Hai Zhuge

Published online on March 18, 2013

Updated on February 26, 2016

 

Intelligence will be greatly extended in a complex space consisting of the physical space, social space and cyberspace. Human-Machine-Nature Symbiosis (HMNS) will be an important characteristic of the complex space. This tutorial introduces the basic concepts, visions, challenges, fundamental problems, ideas, methods, implications and practices. The main purpose is to understand the fundamental structure of the complex space and inspire the creation of the new computing paradigm.

Concepts

Symbiosis referred to a mutual benefit or dependence relationship established through long-term interaction between two or more biological species.

In the nature, symbiosis can be either strong or weak. Strong symbiosis determines the survival of species, for example, bees and flowers, flowers are not able to generate seeds without bees and bees cannot generate honey without flowers. Weak symbiosis widely exists in the nature, for example, between crocodiles and plover birds, which benefit each other but do not heavily relying on each other.

The nature provides the material basis for the generation and development of living beings. Interactions between various individuals in the natural physical space has generated and evolved many spaces. Human society is such a space where human being lives, works and evolves with the physical space and creating more and more artificial spaces.

Thousands of years¡¯ social development generated versatile social units such as communities, professions, functions, and roles, one is related to the other. Some relations enable social units benefit each other as symbiosis in the nature. For example, students and teachers constitute a symbiotic relation. Banks and customers constitute a symbiotic relation. Different from symbiosis in the nature, the symbiosis in society is built by human and symbiotic relations can form a complex symbiosis network, for example, industrial symbiotic network.

The progress of human society has created an artifact space. Artifacts include tools, houses, roads, bridges, and various machines, which are objects in the physical space and have functions and roles in social space.

With the generation and development of information technology, a cyberspace has been created to hold digital objects. The development of various sensors, mobile devices and communication networks enables cyberspace to connect physical space and social space to form a complex space. Interactions and behaviors in one space may have influence in another space. Symbiosis will be an important relation of the complex space.

The following figure depicts a scenario of Human-Machine-Nature Symbiosis.

Human-Machine-Nature Symbiosis is a study of various interactions among species (communities or certain classifications) in social space, cyberspace and the nature, the impacts of interactions and changes, and the design and analysis of various symbiosis networks.

Challenge

Human beings will live and harmoniously develop with various human-machine-nature symbiotic relations in the cyber-physical-social space. Exploring the special symbiotic relation can help deepen the understanding of the space. Research concerns multiple disciplines and will go beyond the ideals of pioneers of computing such as Bush, Turing and Licklider.

Contents

This tutorial emphasizes on challenges, fundamental problems, ideas, methods, principles, implications and practices while introducing concepts and ideas. Presentation includes the following points:
(1) Natural symbiosis.
(2) Man-computer symbiosis.
(3) Pioneers¡¯ visions in computing (Turing, Bush, McCarthy, etc.).
(4) Human-Machine-Nature Symbiosis.
(5) Cyber-Physical-Socio Intelligence.
(6) Industrial symbiosis and material flow.
(7) Knowledge flow network.

Relevant Concepts

Man-Computer Symbiosis

The general-purpose computers are designed for solving problems or processing data according to procedures, predetermined by human. All the alternatives must be foreseen in advance. However, many problems that can be thought through in advance are difficult to think through in advance.

Licklider proposed man-computer symbiosis to enable computers to facilitate formulative thinking, and to enable men and computers to cooperate in making decisions and controlling complex situations without relying on predetermined programs. Men set the goals, propose the hypotheses, determine the criteria, and carry out the evaluations while computers perform the routine work that is necessary to prepare the way for insights and decisions in technical and scientific thinking. This symbiosis was expected to perform intellectual operations much more effectively than man alone can perform them [Licklider, 1960]. Although many pre-request techniques have been realized, computers are still unable to involve in human real-time thinking.

Cyber-Physical Society

Cyber-Physical Society is a multi-dimensional complex space that generates and evolves diverse subspaces to contain different types of individuals interacting with, reflecting or influencing each other directly or through the cyber, physical, socio and mental subspaces. Versatile individuals and socio roles coexist harmoniously yet evolve, provide appropriate on-demand information, knowledge and services for each other, transform from one form into another, interact with each other through various links, and self-organize according to socio value chains. It ensures healthy and meaningful life of individuals, and maintains a reasonable rate of expansion of individuals in light of overall capacity and the material, knowledge, and service flow cycles.

Human-Machine-Nature Symbiosis is an important relation that can help realize harmonious development of Cyber-Physical Society.

Relevant Links

[1] H. Zhuge, Mapping Big Data into Knowledge Space, https://www.youtube.com/watch?v=llKmkgqHLtQ.
[2] Cyber-Physical Society Website. http://www.knowledgegrid.net/~H.Zhuge/CPS.htm.
[3] ACM Distinguished Lectures on Cyber-Physical Society, Knowledge Grid Methodology, and Interactive Semantics.http://dsp.acm.org/view_lecturer.cfm?lecturer_id=2685.

Further Readings

[1] M.R. Chertow, Industrial Symbiosis: Literature and Taxonomy, Annual Review of Energy and the Environment, vol. 25, pp.313-337, 2000.

[2] I. Foster, Human-Machine Symbiosis, 50 Years On, arxiv.org/abs/0712.2255.

[3] T. E. Graedel and B.R. Allenby, Industrial Ecology and Sustainable Engineering, Prentice Hall, 2010.

[4] J. C. R. Licklider, Man-Computer Symbiosis, IRE Transactions on Human Factors in Electronics, vol. HFE-1, pages 4-11, March 1960.

[5] M. Minsky, The Society of Mind. Simon and Schuster, New York. March 15, 1988.

[6] A. Turing, Computing machinery and intelligence, Mind, 59(236)(1950)433-460.

[7] H. Zhuge, Multi-Dimensional Summarization in Cyber-Physical Society: Toward a New Paradigm, Elsevier, 2016.

[8] H. Zhuge, The Knowledge Grid: Toward the Cyber-Physical Society, World Scientific, 2004 (1st edition), 2012 (2nd edition).

[9] H. Zhuge and Y. Xing, Probabilistic Resource Space Model for Managing Resources in Cyber-Physical Society, IEEE Transactions on Service Computing, 5(3)(2012)404-421.

[10] H. Zhuge, Semantic Linking through Spaces for Cyber-Physical-Socio Intelligence: A Methodology, Artificial Intelligence, 175(2011)988-1019.

[11] H. Zhuge, Interactive Semantics, Artificial Intelligence, 174(2010)190-204.

[12] H. Zhuge, Communities and Emerging Semantics in Semantic Link Network: Discovery and Learning. IEEE Transactions on Knowledge and Data Engineering. 21(6)(2009)785-799.

[13] H. Zhuge, The Web Resource Space Model, Springer, 2008.

[14] H. Zhuge, Discovery of knowledge flow in science. Communications of the ACM, 49(5) (2006)101-107.

[15] H. Zhuge, Exploring an epidemic in an e-science environment. Communications of the ACM, 48(9)(2005) 109-114.

[16] H. Zhuge, The Future Interconnection Environment. IEEE Computer, 38(4)(2005) 27-33.

[17] H. Zhuge and X. Shi, Toward the eco-grid: a harmoniously evolved interconnection environment. Communications of the ACM, 47(9)(2004)78-83.


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