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Bibliographic Details
Main Authors: Montazeri, Sina, Mirzaeinia, Akram, Mirzaeinia, Amir
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.03338
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Table of Contents:
  • In prior methods, it was observed that the application of Convolutional Neural Networks agent in Deep Reinforcement Learning to financial data resulted in an enhanced reward. In this study, a specific permutation was applied to the feature vector, thereby generating a CNN matrix that strategically positions more pertinent features in close proximity. Our comprehensive experimental evaluations unequivocally demonstrate a substantial enhancement in reward attainment.