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CHAPTER


                  Third Gen AI as Human

                  Experience Based Expert                                    3

                  Systems



                                                               a
                                                      Harold Szu , The Al Working Group b
                                         Catholic University of America, Washington, DC, United States


                  CHAPTER OUTLINE
                  1. Introduction .........................................................................................................53
                  2. Third Gen AI.........................................................................................................56
                    2.1 MaxwelleBoltzmann Homeostasis .......................................................... 61
                    2.2 The Inverse Is Convolution Neural Networks ............................................ 63
                    2.3 Fuzzy Membership Function (FMF and Data Basis) .................................. 67
                  3. MFE Gradient Descent...........................................................................................70
                    3.1 Unsupervised Learning Rule................................................................... 70
                  4. Conclusion ..........................................................................................................74
                  Acknowledgment.......................................................................................................77
                  References ...............................................................................................................77
                  Further Reading ........................................................................................................78


                  1. INTRODUCTION
                  What started the third Gen of AI? Shortfalls of driverless autonomous vehicles
                  (DAV) coexisted with human psychological behaviors.




                  a
                  Theory led by Lin-Ching Chang; Jeff Jenkins, Binh Tran, Hong Yu, Lu Feng, Simon Foo, Soo-Young
                  Lee, Guna Seetharaman, Modeling led by Mike Wardlaw; Yufeng Zheng, Anke Meyer-Base, Henry
                  Chu, John Gray, Charles Hsu, Implementation led by Ming Kai Hsu; Joseph Landa, Richard Messner,
                  Gyu Moon, Jerry Wu, Shiqiong Susan Young.
                  b
                  The AI Working Group: Lin-Ching Chang, Jeffery Jenkins, Harold Szu, Binh Tran, Hong Yu, CUA,
                  Washington, DC; Lu Feng, Am U., Washington, DC; Simon Foo, FAMU, Capital Tallahassee,
                  FL (foo@eng.famu.fsu.edu)); Soo-Young Lee, Korean Advanced Institute Science Technology, Tai-
                  chung, South Korea; Guna Seetharaman, NRL, Washington, DC; Mike Wardlaw, ONR, Arlington,
                  VA; Yufeng Zheng (http://ica-wavelet.org) Alcon U.; Anke Meyer-Baese, FSU, FL; Henry Chu, UL
                  Lafayette, LA (chu@louisiana.edu); John E. Gray, Naval Surface Warfare Center Dahlgren Division,
                  VA, Charles Hsu, Ming-Kai Hsu, GWU, Washington, DC; Joseph Landa, Briartek, Arlington, VA:
                  Anke Meyer-Baese, FSU, FL; Richard Messner, UNH, Gyu Moon, Hallym U.; Jerry Wu, Univ. of
                  Maryland College Park, MD; Shiqiong Susan Young, ARL, MD.
                                                                                          53
                  Artificial Intelligence in the Age of Neural Networks and Brain Computing. https://doi.org/10.1016/B978-0-12-815480-9.00003-7
                  Copyright © 2019 Elsevier Inc. All rights reserved.
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