Deep Reinforcement Learning Libraries and Deep Reinforcement Learning in Finance

  • 📰 hackernoon
  • ⏱ Reading Time:
  • 26 sec. here
  • 2 min. at publisher
  • 📊 Quality Score:
  • News: 14%
  • Publisher: 51%

Canada News News

Canada Canada Latest News,Canada Canada Headlines

Explore the landscape of open-source DRL libraries for finance, including OpenAI Gym, Google Dopamine, RLlib, and TensorLayer

Authors: Xiao-Yang Liu, Hongyang Yang, Columbia University ; Jiechao Gao, University of Virginia ; Christina Dan Wang , New York University Shanghai . Table of Links Abstract and 1 Introduction 2 Related Works and 2.1 Deep Reinforcement Learning Algorithms 2.2 Deep Reinforcement Learning Libraries and 2.3 Deep Reinforcement Learning in Finance 3 The Proposed FinRL Framework and 3.1 Overview of FinRL Framework 3.2 Application Layer 3.3 Agent Layer 3.4 Environment Layer 3.

1 Deep Reinforcement Learning Algorithms 2 Related Works and 2.1 Deep Reinforcement Learning Algorithms 2.2 Deep Reinforcement Learning Libraries and 2.3 Deep Reinforcement Learning in Finance 2.2 Deep Reinforcement Learning Libraries and 2.3 Deep Reinforcement Learning in Finance 3 The Proposed FinRL Framework and 3.1 Overview of FinRL Framework 3 The Proposed FinRL Framework and 3.1 Overview of FinRL Framework 3.2 Application Layer 3.2 Application Layer 3.3 Agent Layer 3.3 Agent Layer 3.

 

Thank you for your comment. Your comment will be published after being reviewed.
Please try again later.
We have summarized this news so that you can read it quickly. If you are interested in the news, you can read the full text here. Read more:

 /  🏆 532. in CA

Canada Canada Latest News, Canada Canada Headlines

Similar News:You can also read news stories similar to this one that we have collected from other news sources.

Deep Reinforcement Learning Framework to Automate Trading in Quantitative FinanceFinRL is an open-source framework for quantitative traders, simplifying DRL strategy development with customizable, reproducible, and beginner-friendly tools.
Source: hackernoon - 🏆 532. / 51 Read more »