Abstract
In the twentieth century, AI (artificial Intelligence) arose along with Turing’s theory of computability. AI-research was focused on using symbolic representations in computer programs to model human cognitive abilities. The final goal was a complete symbolic representation of human intelligence in the sense of Turing’s AI-test. Actually, human intelligence is only a special example of problem solving abilities which have evolved during biological evolution. In embodied AI and robotics, the emergence of intelligence is explained by bodily behavior and interaction with the environment. But, intelligence is not reserved to single organisms and brains. In a technical coevolution, computational networks grow together with technical and societal infrastructures generating automated and intelligent activities of cyberphysical systems. The article argues for a unified theory of intelligent complex systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
acatech (Ed.). (2011). Cyberphysical systems. acatech position (acatech = National Academy of Science and Technology). Berlin: Springer.
Albert, R., & Barabási, A.-L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47–97.
Balch, T., & Parker, L. (Eds.). (2002). Robot teams: From diversity to polymorphism. Wellesley: A. K. Peters.
Bekey, G. L. (2005). Autonomous robots. From biological inspiration to implementation and control. Cambridge, MA: MIT Press.
Bellman, K. L. (2005). Self-conscious modeling. IT – Information Technology, 4, 188–194.
Berners-Lee, T. (1999). Weaving the web: The original design and ultimate destiny of the world wide web by the inventor. San Francisco: Harper Collins.
Braitenberg, V., & Radermacher, F. J. (Eds.). (2007). Interdisciplinary approaches to a new understanding of cognition and consciousness. Universitätsverlag Ulm: Ulm.
Brooks, R. A. (1999). Cambrian intelligence: The early history of the new AI. Cambridge, MA: The MIT Press.
Chalmers, D. (2010). The character of consciousness. Oxford: Oxford University Press.
CoTeSys. (2006–2011). is funded by the German Research Council DFG as a research cluster of excellence within the “excellence initiative” from 2006–2012.
Cyber-Physical Systems. Program announcements & information. The National Science Foundation, Arlington, 30 Sept 2008.
Dreyfus, H. L. (1979). What computer’s can’t do – The limits of artificial intelligence. New York: Harper & Row.
Dreyfus, H. L. (1982). Husserl, intentionality, and cognitive science. Cambridge, MA: MIT Press.
Freeman, W. J. (2004). How and why brains create meaning from sensory information. International Journal of Bifurcation and Chaos, 14, 515–530.
Friederici, A. D. (2006). The neural basis of language development and its impairment. Neuron, 52, 941–952.
Haken, H. (1996). Principles of brain functioning. A synergetic approach to brain activity, behaviour and cognition. Berlin: Springer.
Hansmann, U. (2001). Pervasive computing handbook. Berlin: Springer.
Hebb, D. O. (1949). The organization of the behavior. New York: Wiley.
Lee, E. (2008). Cyber-physical systems: Design challenges. In University of California, Berkeley Technical Report No. UCB/EECS-2008-8.
Mainzer, K. (2003). KI – Künstliche intelligenz. Grundlagen intelligenter systeme. Darmstadt: Wissenschaftliche Buchgesellschaft.
Mainzer, K. (2007). Thinking in complexity. The computational dynamics of matter, mind, and mankind (5th ed.). New York: Springer.
Mainzer, K. (2008a). The emergence of mind and brain: An evolutionary, computational, and philosophical approach. In R. Banerjee & B. K. Chakrabarti (Eds.), Models of brain and mind. Physical, computational and psychological approaches (pp. 115–132). Amsterdam: Elsevier.
Mainzer, K. (2008b). Organic computing and complex dynamical systems. Conceptual foundations and interdisciplinary perspectives. In R. P. Würtz (Ed.), Organic computing (pp. 105–122). Berlin: Springer.
Mainzer, K. (2009). From embodied mind to embodied robotics: Humanities and system theoretical aspects. Journal of Physiology, Paris, 103, 296–304.
Mainzer, K. (2010). Leben als Maschine? Von der Systembiologie zur Robotik und Künstlichen Intelligenz. Paderborn: Mentis.
Mainzer, K. (2014). Die Berechnung der Welt. Von der Weltformel zu Big Data. München: C.H. Beck.
Mainzer, K., & Chua, L. O. (2011). The universe as automaton. From simplicity and symmetry to complexity. Berlin: Springer.
Mainzer, K., & Chua, L. O. (2013). Local activity principle. London: Imperial College Press.
Mataric, M., Sukhatme, G., & Ostergaard, E. (2003). Multi-robot task allocation in uncertain environments. Autonomous Robots, 14(2–3), 253–261.
Merleau-Ponty, M. (1962). Phenomenology of perception. London: Kegan Paul.
Nolfi, S., & Floreano, D. (2001). Evolutionary robotics. The biology, intelligence, and technology of self-organizing machines. Cambridge, MA: MIT Press.
Pfeifer, R., & Scheier, C. (2001). Understanding intelligence. Cambridge, MA: MIT Press.
Scott, A. (2003). Nonlinear science. Emergence and dynamics of coherent structures. Oxford: Oxford University Press.
Shuji Kajita. (2007). Humanoide roboter. Theorie und Technik des Künstlichen Menschen. Berlin: Aka GmbH.
Singer, W. (1994). The role of synchrony in neocortical processing and synaptic plasticity. In E. Domany, L. van Hemmen, & K. Schulten (Eds.), Models of neural networks II. Berlin: Springer.
Tarski, A. (1935). Der Wahrheitsbegriff in den formalisierten Sprachen. Studia Philosophica, 1, 261–405.
Thrun, S., Burgard, W., & Fox, D. (2005). Probabilistic robotics. Cambridge, MA: MIT Press.
Wedde, H. J., Lehnhoff, S., Rehtanz, C., & Krause, O. (2008). Von eingebetteten Systemen zu Cyber-Physical Systems. Eine neue Forschungsdimension für verteilte eingebettete Realzeitsysteme. In Pearl 2008 – Informatik Aktuell. Aktuelle Anwendungen in Technik und Wirtschaft 2007 12.
Weiser, M. (1991). The computer for the 21st century. Scientific American, 9, 66–75.
Wilson, E. O. (2000). Sociobiology: The new synthesis (25th ed.). Cambridge, MA: Harvard University Press.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Mainzer, K. (2016). Toward a Theory of Intelligent Complex Systems: From Symbolic AI to Embodied and Evolutionary AI. In: Müller, V.C. (eds) Fundamental Issues of Artificial Intelligence. Synthese Library, vol 376. Springer, Cham. https://doi.org/10.1007/978-3-319-26485-1_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-26485-1_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26483-7
Online ISBN: 978-3-319-26485-1
eBook Packages: Religion and PhilosophyPhilosophy and Religion (R0)