Expanding the Breadth of Ability in Artificial Intelligence Systems with Decision Trees

  •  Andrew McInnis Jr    
  •  Mohammad Alshibli    
  •  Ahmad Alzaghal    
  •  Samir Hamada    


This paper introduces a unique perspective. Rather than focusing on improving the already significant achievements of existing artificial intelligence algorithms, it investigates the potential of merging various algorithms to enhance their overall capabilities. Essential design aspects required for this integration are examined, and a prototype system is developed to demonstrate the practical application of these design principles. This method aims to broaden the range of capabilities accessible to a system, addressing the limitation of the narrow focus prevalent in contemporary artificial intelligence.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: semiannual

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