Going beyond Computation and Its Limits: Injecting Cognition into Computing
Rao Mikkilineni
Kawa Objects, Los Altos, USA.
DOI: 10.4236/am.2012.331248   PDF    HTML   XML   5,881 Downloads   8,736 Views   Citations

Abstract

Cognition is the ability to process information, apply knowledge, and change the circumstance. Cognition is associated with intent and its accomplishment through various processes that monitor and control a system and its environment. Cognition is associated with a sense of “self” (the observer) and the systems with which it interacts (the environment or the “observed”). Cognition extensively uses time and history in executing and regulating tasks that constitute a cognitive process. Whether cognition is computation in the strict sense of adhering to Turing-Church thesis or needs additional constructs is a very relevant question for addressing the design of self-managing (autonomous) distributed computing systems. In this paper we argue that cognition requires more than mere book-keeping provided by the Turing machines and certain aspects of cognition such as self-identity, self-description, self-monitoring and self-management can be implemented using parallel extensions to current serial von-Neumann stored program control (SPC) Turing machine implementations. We argue that the new DIME (Distributed Intelligent Computing Element) computing model, recently introduced as the building block of the DIME network architecture, is an analogue of Turing’s O-machine and extends it to implement a recursive managed distributed computing network, which can be viewed as an interconnected group of such specialized Oracle machines, referred to as a DIME network. The DIME network architecture provides the architectural resiliency, which is often associated with cellular organisms, through auto-failover; auto-scaling; live-migration; and end-to-end transaction security assurance in a distributed system. We argue that the self-identity and self-management processes of a DIME network inject the elements of cognition into Turing machine based computing as is demonstrated by two prototypes eliminating the complexity introduced by hypervisors, virtual machines and other layers of ad-hoc management software in today’s distributed computing environments.

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R. Mikkilineni, "Going beyond Computation and Its Limits: Injecting Cognition into Computing," Applied Mathematics, Vol. 3 No. 11A, 2012, pp. 1826-1835. doi: 10.4236/am.2012.331248.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] P. Cockshott, L. M. MacKenzie and G. Michaelson, “Computation and Its Limits,” Oxford University Press, Oxford, 2012.
[2] J. V. Neumann, “Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components,” In: C. E. Shannon and J. McCarthy, Eds., Automatic Studies, Princeton University Press, Princeton, 1956, pp. 43-98.
[3] W. Aspray and A. Burks, “Papers of John von Neumann on Computing and Computer Theory,” MIT Press, Cambridge, 1989.
[4] A. M. Turing, “The Essential Turing,” Oxford University Press, Oxford, 2004.
[5] A. M. Turing, “Computing Machinery and Intelligence,” Mind, Vol. 49, 1950, pp. 433-460. doi:10.1093/mind/LIX.236.433
[6] P. Stanier and G. Moore, “Embryos, Genes and Birth Defects,” 2nd Edition, John Wiley & Sons, London, 2006, p. 5.
[7] S. B. Caroll, “The New Science of Evo Devo—Endless Forms Most Beautiful,” W. W. Norton & Co., New York, 2005.
[8] A. M. Turing, “Systems of Logic Defined by Ordinals,” Proceedings London Mathematical Society, Vol. 2, No. 45, 1939, pp. 161-228.
[9] B. J. Copeland, “Turing’s O-Machines, Searle, Penrose and the Brain,” Analysis, Vol. 58, 1998, pp. 128-138. doi:10.1093/analys/58.2.128
[10] H. R. Maturana, “Biological Computer Laboratory Research Report BCL 9.0,” University of Illinois, Urbana, 1970.
[11] H. R. Maturana and F. J. Varela, “Autopoiesis and Cognition: The Realization of the Living (Boston Studies in the Philosophy of Science),” D. Reidel, Dordrecht, 1960.
[12] E. Thompson, “Mind in Life: Biology, Phenomenology, and the Sciences of the Mind,” Harvard University Press, Cambridge, 2007.
[13] P. Johnson-Laird, “How Could Consciousness Arise from the Computations of the Brain?” In: C. Blakemore and S. Greenfield, Eds., Mindwaves, Basil Blackwell, Oxford, 1987.
[14] R. Mikkilineni, “Designing a New Class of Distributed Systems,” Springer, New York, 2011. doi:10.1007/978-1-4614-1924-2
[15] R. Mikkilineni, A. Comparini and G. Morana, Turing O-Machine and the DIME Network Architecture: Injecting the Architectural Resiliency into Distributed Computing, in Turing-100,” In: A. Voronkov, Ed., EPIC Series, Easy Chair, 2012. http://www.easychair.org/publications/?page=877986046
[16] A. M. Turing, “The Essential Turing,” Oxford University Press, Oxford, 2004.
[17] G. Piccinini, “Alan Turing and the Mathematical Objection,” Minds and Machines, Vol. 13, No. 1, 2003, pp. 23-48. doi:10.1023/A:1021348629167
[18] A. M. Turing, “Systems of Logic Defined by Ordinals,” Proceedings London Mathematical Society, Vol. 45, 1939, pp. 161-228.
[19] S. Feferman, “Turing’s Thesis,” Notices of the AMS, Vol. 53, No. 10, 2006, p. 2.
[20] R. Soare, “Turing Oracle Machines, Online Computing, and Three Displacements in Computability Theory,” Annals of Pure and Applied Logic, Vol. 160, No. 3, 2009, pp. 368-399. doi:10.1016/j.apal.2009.01.008
[21] A. Kurakin, “Retrieved from the Universal Principles of Self-Organization and the Unity of Nature and Knowledge,” 2007. http://www.alexeikurakin.org/text/thesoft.pdf
[22] A. Kurakin, “Theoretical Biology and Medical Modeling,” 2011. http://www.tbiomed.com/content/8/1/4
[23] R. Milner, “Communicating and Mobile Systems: The PiCalculus,” Cambridge University Press, Cambridge, 1999.
[24] P. Goyal and R. Mikkilineni, “Implementing Managed Loosely-coupled Distributed Business Processes: A New Approach using DIME Networks, Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE),” 21st IEEE International Conference, Toulouse, 25-27 June 2012.
[25] P. Goyal, “A Recursive Computing Model for DIME Network Architecture Using π-Calculus,” Private Communication, 2012.
[26] R. Mikkilineni and I. Seyler, “A New Operating System for Scalable, Distributed, and Parallel Computing,” IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum (IPDPSW), Anchorage, 16-20 May 2011, pp. 976-983.
[27] R. Mikkilineni and I. Seyler, “Implementing Distributed, Self-Managing Computing Services Infrastructure Using a Scalable, Parallel and Network-centric Computing Model,” In: M. Villari, C. I. Brandic and F. Tusa, Eds., Achieving Federated and Self-Manageable Cloud Infrastructures: Theory and Practice, IGI Global, pp. 57-78.
[28] R. Mikkilineni, I. Seyler, G. Morana, D. Zito and M. Di Sano, “Service Virtualization Using a Non-Von Neumann Parallel, Distributed, and Scalable Computing Model,” Journal of Computer Networks and Communications, 2012, in Press.
[29] G. Morana and R. Mikkilineni, “Scaling and Self-Repair of Linux Based Services Using a Novel Distributed Computing Model Exploiting Parallelism,” 20th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), Paris, 27-29 June 2011, pp. 98-103.
[30] A. Wells, “Rethinking Cognitive Computation: Turing and the Science of Mind,” Palgrave Macmillan, London, 2006.
[31] L. Barrett, “Beyond the Brain,” Princeton University Press, Princeton, 2011.
[32] M. Mitchell-Waldrop, “Complexity: The Emerging Science at the Edge of Order and Chaos,” Penguin Books, London, 1992, p. 218.

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