Project for Course : Reinforcement Learning
How to Run code:
Using Google Colab Platform:
Place data in Data Folder in drive folder RL Project. The path to your data should look like - My Drive/RL Project/Data
The Notebook is in the RL Project Folder. Run the cells in sequence
Using an IDE:
Download the data from the link referred below Change the paths in the python folder to the path to the data
On windows the path could look like: r'C:\Users\HOME\Documents\RLProject\Data\ml-1m'
Install the dependencies - pytorch,torch,sklearn,numpy,pandas,scipy,matplotlib,tqdm they are mentioned at the top of the python file
Run python -W ignore rl_actorcritic_ddpg_movie_recommendation.py
Implementation of Paper: Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling. Ref: Liu, Feng & Tang, Ruiming & Li, Xutao & Ye, Yunming & Chen, Haokun & Guo, Huifeng. (2018). Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling.
Dataset Link: https://grouplens.org/datasets/movielens/1m/
Dataset Reference: F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4, Article 19 (December 2015), 19 pages. DOI=http://dx.doi.org/10.1145/2827872
Other References:
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@misc{RecNN, author = {M Scherbina}, title = {RecNN: RL Recommendation with PyTorch}, year = {2019}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/awarebayes/RecNN}}, }
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https://github.com/shashist/recsys-rl/tree/35b12eb775baa4cb2dc573df3964c7f84cbcc98b