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Intelligent control using generalizing case-based reasoning with neural networks


Babcock, David S. (2000) Intelligent control using generalizing case-based reasoning with neural networks. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/HBTD-WE62.


One model of human learning involves choosing an action based on past experiences in similar situations. The chosen action is typically modified to compensate for any discrepancies with the current situation. After sufficient experience has been obtained, at least in a particular regime, the experiences are conceptualized into a general response mechanism. This thesis presents an algorithm that formalizes this hybrid reasoning process and applies it to control of a nonlinear physical system. Experiences are stored as vectors of variables known as cases in a set called a casebase. Vector norms are used to select an appropriate case from the case base which is then modified using an adaptation routine. Once the modified action is applied to the system and the resulting outcome is observed, the casebase is augmented to include the new experience for improved future performance. A gated expert neural network is eventually trained on subsets of the case base to create local inverse model approximations for regions of the input space where sufficient data is available to support generalization. The gate network selects one of the experts if appropriate or otherwise defaults back to case-based reasoning. The applicability of the hybrid algorithm is demonstrated on a nonlinear control problem, setpoint regulation in a ball and beam system.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Electrical Engineering
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Electrical Engineering
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Goodman, Rodney M.
Thesis Committee:
  • Unknown, Unknown
Defense Date:22 February 2000
Record Number:CaltechTHESIS:09302010-142626064
Persistent URL:
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:6079
Deposited On:30 Sep 2010 22:48
Last Modified:21 Dec 2019 02:52

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