Main Reference PaperUsing Deep Q-learning to understand the tax evasion behavior of risk-averse firms, Expert Systems With Applications, 2018 [Java/Python/R].
  • By employing the deep Q-learning, the proposed method recognizes the behavior of tax evasion in the risk-averse firm. It mitigates the computation complexity by utilizing the Markov dynamical model.

+ Description
  • By employing the deep Q-learning, the proposed method recognizes the behavior of tax evasion in the risk-averse firm. It mitigates the computation complexity by utilizing the Markov dynamical model.

  • To decide the behavior of tax evasion

  • To increase the long-term revenue

+ Aim & Objectives
  • To decide the behavior of tax evasion

  • To increase the long-term revenue

  • The learning improves by utilizing the efficient actor-critic algorithm with experience replay

+ Contribution
  • The learning improves by utilizing the efficient actor-critic algorithm with experience replay

  • Operating system: Ubuntu / Windows

  • Java/Python/R

+ Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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