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This repo is really great and helpful! I enjoy working with that. Thank you for your great work:)
I find your repo so potential and I wonder if you have a plan to support some new algorithms such a…
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Hello, I'm still learning how reinforcement algorithms tie in to neural networks, and am wondering if/how this could tie in to a tensor flow neural network / layers model?
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What is the size unit of the map in the current scene design?
What is the distance that the agent moves each time, and what is its unit?
Is the current map continuous or grid-designed?
Yu-zx updated
4 hours ago
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I'm curious if this project will follow up by designing defender as an agent that can be trained with reinforcement learning algorithms and how we will achieve this based on the existing environment? …
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Material Outline for notebook #3
* Introducing Radiation Emulation Dataset
* Overview (topoography) of machine learning algorithms/techniques
* Decision Trees and Derivatives
* Neural Networks
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### List of algorithms
- VPG: Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning (IROS2018) [paper](https://vpg.cs.princeton.edu/paper.pdf)
- DIPN: Deep…
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* https://github.com/zhoubolei/introRL
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# The Effect of Different Reinforcement Learning Algorithms on the Performance of AI for Lunar Lander
## TITLE
The Effect of Different Reinforcement Learning Algorithms on the Performance of AI fo…
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Traditional recommendation system based on the user rating on the similar items.
So, we can predict the user rating on an unrated item based on the his rates with the similar items.
source : htt…
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Increase the training iterations: Train the PPO model for more iterations, as the model might not have converged yet.
Adjust the PPO hyperparameters: Experiment with different hyperparameters such …