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Cognitive Intelligence and the Brain: Synthesizing Human Brain Functions

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Artificial Cognition Architectures

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Abstract

In order for a SELF to function autonomously, and have the abilities to learn, reason, infer, evolve, perform self-assessment and self-actuation, we propose a cognitive framework similar to the human brain. What we describe in this chapter is an Artificial Cognitive Neural Framework (ACNF) that provides the ability to organize information semantically into meaningful fuzzy concepts and information fragments that create cognitive hypotheses as part of a SELF’s topology [129], similar to human processing. This approach addresses the problems of autonomous information processing by accepting that the system must purposefully communicate concepts fuzzily within its processing system, often inconsistently, in order to adapt to a changing real-world, real-time environment. Additionally, we describe a processing framework that allows a SELF to deal with real-time information environments, including heterogeneous types of fuzzy, noisy, and obfuscated data from a variety of sources with the objective of improving actionable decisions using Recombinant kNowledge Assimilation (RNA) processing [70, 71] integrated within an ACNF to recombine and assimilate knowledge based upon human cognitive processes. The cognitive processes are formulated and embedded in a neural network of genetic algorithms and stochastic decision making with the goal of recombinantly minimizing ambiguity and maximizing clarity while simultaneously achieving a desired result [58, 95].

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References

  1. Ackley D, Litman M (2002) Interactions between learning and evolution. Artificial life XII. Addison-Wesley

    Google Scholar 

  2. Beer R (2005) Computational and dynamical languages for autonomous agents. In: Port RF, van Gelder T (eds)

    Google Scholar 

  3. Beer R, Gallagher J (2002) Evolving dynamical neural networks for adaptive behavior. Adapt Behav 61(1):91–122

    Google Scholar 

  4. Belew R (2002) Evolving networks: using genetic algorithms with connectionist learning. In: Artificial life XII

    Google Scholar 

  5. Bishop CM (1995) Neural networks for pattern recognition. Oxford University Press, New York

    Google Scholar 

  6. Cliff D, Harvey I (2002) Incremental evolution of neural network architectures for adaptive behavior. Technical Report, University of Sussex, COGS

    Google Scholar 

  7. Crowder J (2001) ELYSE, The evolving, life-like yielding, symbiotic environment. NSA Technical Paper Technical Paper TIT_01_01_013_2001_002

    Google Scholar 

  8. Crowder J (2001) Integrating an expert system into a neural network with genetic programming for process planning. NSA Technical Paper TIT_01_01_013_2001_001

    Google Scholar 

  9. Crowder J (2001) Statistical performance of outer product associative memory models. GDIS, IRAD Report GDIS_9873_2001_001

    Google Scholar 

  10. Crowder J (2002) Derivation of fuzzy classification rules from multidimensional data. NSA Technical paper CON_0013_2002_001

    Google Scholar 

  11. Crowder J (2002) Adaptive learning algorithms for functional constraints on an evolving neural network system. NSA Technical paper CON_0013_2002_003

    Google Scholar 

  12. Crowder J (2003) Machine learning: intuition (concept) learning in hybrid genetic/fuzzy/neural systems. NSA Technical paper CON_0013_2003_009

    Google Scholar 

  13. Crowder J (2005) Cognitive systems for data fusion. In: Proceedings of the 2005 PSTN processing technology conference, Ft. Wayne

    Google Scholar 

  14. Crowder J (2010) Flexible object architectures for hybrid neural processing systems. In: Proceedings of the 12th annual international conference on artificial intelligence, Las Vegas

    Google Scholar 

  15. Crowder J (2010) The continuously recombinant genetic neural fiber network. In: Proceedings for the AIAA Infotech@Aerospace 2010 conference, Atlanta

    Google Scholar 

  16. Crowder J (2012) Real-time data storage and retrieval in autonomous robotic systems. In: Proceedings of the 1st international conference on robotic intelligence and applications, Gwanju

    Google Scholar 

  17. Crowder J, Carbone J (2011) Occam learning through pattern discovery: computational mechanics in AI systems. In: Proceedings of the 13th annual international conference on artificial intelligence, Las Vegas

    Google Scholar 

  18. Crowder J, Carbone J (2011) The great migration: information to knowledge using cognition-based frameworks. Springer Science, New York

    Google Scholar 

  19. Crowder J, Friess S (2012) Extended metacognition for artificially intelligent systems (AIS): artificial locus of control and cognitive economy. In: Proceedings of the 13th annual international conference on artificial intelligence, Las Vegas

    Google Scholar 

  20. Crowder J, Friess S (2010) Artificial neural diagnostics and prognostics: self-soothing in cognitive systems. In: Proceedings of the 12th annual international conference on artificial intelligence, Las Vegas

    Google Scholar 

  21. Crowder J, Friess S (2010) Artificial neural emotions and emotional memory. In: Proceedings of the 12th annual international conference on artificial intelligence, ICAI’10

    Google Scholar 

  22. Crowder J, Friess S (2011) The artificial prefrontal cortex: artificial consciousness. In: Proceedings of the 13th annual international conference on artificial intelligence, Las Vegas

    Google Scholar 

  23. Crowder J, Friess S (2011) Metacognition and metamemory concepts for AI systems. In: Proceedings of the 13th annual international conference on artificial intelligence, Las Vegas

    Google Scholar 

  24. Crowder J, Scally L, Bonato M (2012) Applications for intelligent information agents (I2As): learning agents for autonomous space asset management (LAASAM). In: Proceedings of the international conference on artificial intelligence, ICAI’12, Las Vegas

    Google Scholar 

  25. Crowder J, Friess S (2013) Systems engineering agile design methodologies. Springer, New York. ISBN 978-1-4614-6662-8

    Google Scholar 

  26. Damasio A (1994) Descarte’s error: emotion, reason, and the human brain. Gosset/Putnam, New York

    Google Scholar 

  27. Davis M, Whalen P (2001) The amygdala: vigilance and emotion. Mol Psychiatry 6:13–34

    Article  Google Scholar 

  28. Davis L (1991) The handbook of genetic algorithms. Van Nostrand Reinhold, New York

    Google Scholar 

  29. DeYoung C, Hirsh J, Shane M, Papademetris X, Rajeevan N, Gray J (2010) Testing predictions from personality neuroscience. Psychol Sci 21(6):820–828

    Article  Google Scholar 

  30. Eichenbaum H (2002) The cognitive neuroscience of memory. Oxford University Press, New York

    Book  Google Scholar 

  31. Emery M (2000) A discrete approach to the chaotic representation property. 005, IRMA

    Google Scholar 

  32. Harmon S (2011) Human perception of gendered artificial entities. Colby College, Waterville

    Google Scholar 

  33. Holland JH, Reitman JS (1978) Cognitive systems based on adaptive algorithms. In: Waterman DA, Hayey-Roth F (eds) Pattern directed inference systems. Academic, New York, pp 313–329

    Google Scholar 

  34. Holland P, Gallagher M (2004) Amygdala-frontal interactions and reward expectancy. Curr Opin Neurobiol 14:148–155

    Article  Google Scholar 

  35. Jacobs R, Jordan M, Nowlan S, Hinton G (1991) Adaptive mixtures of local experts. Neural Comput 3

    Google Scholar 

  36. Kosko G (2002) Fuzzy cognitive maps. Int J Man Mach Stud

    Google Scholar 

  37. Kroeker JP (2008) Wiener analysis of functionals of a Markov chain: applications to neural transformations of random signals. Biol Cybern 56:243–248

    MathSciNet  Google Scholar 

  38. LaBar K, Cabeza R (2006) Cognitive neuroscience of emotional memory. Nat Rev Neurosci 7:54–64

    Article  Google Scholar 

  39. LeDoux J (1996) The emotional brain. Simon and Schuster, New York

    Google Scholar 

  40. LeDoux J (2000) Emotion circuits in the brain. Annu Rev Neurosci 23:155–184

    Article  Google Scholar 

  41. Levine P (1997) Walking the tiger: healing trauma. North Atlantic Books, Berkeley

    Google Scholar 

  42. Marsella S, Gratch J (2002) A step towards irrationality: using emotion to change belief. In: 1st international joint conference on autonomous agents and multi-agent systems, Bologna

    Google Scholar 

  43. Michalski R (1993) Inferential theory of learning as a conceptual basis for multi-strategy learning. Mach Learn 11:111–151

    MathSciNet  Google Scholar 

  44. Miller E, Freedman D, Wallis J (2002) The prefrontal cortex: categories, concepts and cognition. Philos Trans R Soc Lond B Biol Sci 357(1424):1123–36

    Article  Google Scholar 

  45. Newell A (2003) Unified theories of cognition. Harvard University Press, Cambridge

    Google Scholar 

  46. Newell A, Shaw J, Simon H (1957) Preliminary description of general problem solving program-i (gps-i). WP7, Carnegie Institute of Technology, Pittsburgh

    Google Scholar 

  47. Raskin V, Taylor JM, Hemplemann CF (2010) Ausocial engineering. New Security Paradigms Workshop, Concord

    Google Scholar 

  48. Scally L, Bonato M, Crowder (2011) Learning agents for autonomous space asset management. In: Proceedings of the advanced maui optical and space surveillance technologies conference, Maui

    Google Scholar 

  49. Taylor JM, Raskin V (2011) Understanding the unknown: unattested input processing in natural language, FUZZ-IEEE conference, Taipei

    Google Scholar 

  50. Thelan E, Smith L (2004) A dynamic systems approach to the development of cognition and action. MIT Press

    Google Scholar 

  51. Wooldridge M (2006) Agents as a Rorschack test: a response to Franklin and Graesser. Springer, London

    Google Scholar 

  52. Wooldridge M, Jennings N (1995) Intelligent agents: theory and practice. Knowl Eng Rev 10(2):115–152

    Article  Google Scholar 

  53. Yang Y, Raine A (November 2009) Prefrontal structural and functional brain imaging findings in antisocial, violent, and psychopathic individuals: a meta-analysis. Psychiatry Res 174(2):81–8. doi:10.1016/j.pscychresns.2009.03.012. PMID 19833485

    Google Scholar 

  54. Sternberg S (1966) High-speed scanning in human memory. Science 153:652–654

    Article  Google Scholar 

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Authors and Affiliations

  1. Englewood, CO, USA

    James A. Crowder

  2. Raytheon Intelligence and Information Systems, McKinney, TX, USA

    John N. Carbone

  3. Relevant Counseling LLC, Englewood, CO, USA

    Shelli A. Friess

Authors
  1. James A. Crowder
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  2. John N. Carbone
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  3. Shelli A. Friess
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Crowder, J.A., Carbone, J.N., Friess, S.A. (2014). Cognitive Intelligence and the Brain: Synthesizing Human Brain Functions. In: Artificial Cognition Architectures. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8072-3_4

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  • DOI: https://doi.org/10.1007/978-1-4614-8072-3_4

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