Fuzzy Controller of Reward of Reinforcement Learning For Handwritten Digit Recognition

Saber Malekzadeh

doi:10.13140/RG.2.2.20222.79688

Fuzzy Controller of Reward of Reinforcement Learning For Handwritten Digit Recognition

Machine Learning 2018-12-19 v1 Computer Vision and Pattern Recognition

Authors: Saber Malekzadeh

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Abstract

Recognition of human environment with computer systems always was a big deal in artificial intelligence. In this area handwriting recognition and conceptualization of it to computer is an important area in it. In the past years with growth of machine learning in artificial intelligence, efforts to using this technique increased. In this paper is tried to using fuzzy controller, to optimizing amount of reward of reinforcement learning for recognition of handwritten digits. For this aim first a sample of every digit with 10 standard computer fonts, given to actor and then actor is trained. In the next level is tried to test the actor with dataset and then results show improvement of recognition when using fuzzy controller of reinforcement learning.

Keywords

fuzzy controller reinforcement learning reward optimization handwritten digit recognition actor machine learning

Cite

@article{arxiv.1812.07028,
  title  = {Fuzzy Controller of Reward of Reinforcement Learning For Handwritten Digit Recognition},
  author = {Saber Malekzadeh},
  journal= {arXiv preprint arXiv:1812.07028},
  year   = {2018}
}

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Submitted to the 3rd International Conference on applied research in Computer Science and Information Technology. in Farsi

Fuzzy Controller of Reward of Reinforcement Learning For Handwritten Digit Recognition

Abstract

Keywords

Cite

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