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https://github.com/borealisai/sasrec-ccql

PyTorch code of "Robust Reinforcement Learning Objectives for Sequential Recommender Systems"
https://github.com/borealisai/sasrec-ccql

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PyTorch code of "Robust Reinforcement Learning Objectives for Sequential Recommender Systems"

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README

          

# SASRec-CCQL

Transformer + RL based Recommender System : See
paper [Robust Reinforcement Learning Objectives for Sequential Recommender Systems
](https://arxiv.org/abs/2305.18820)

![Arch](/results/architecture.png "Arch")

## Installation

Use the `install.sh` script, give it executable permissions with `chmod +x install.sh`, and run it
with `./install.sh`. This uses `conda`.

Tested with the following lib versions:

```
python 3.8.8
torch 1.8.1+cu111
torch-geometric 2.2.0
torch-sparse 0.6.16
torchmetrics 0.3.2
torchvision 0.9.1+cu111
pandas 1.5.2
numpy 1.22.3
CUDA Version: 11.4
```

## Running Experiments

```
python SASRec_ccql.py --dataset=RC15
```

```
python SASRec_ccql.py --dataset=Retailrocket
```

# Results

## Pytorch Baselines

![RC15Top20](results/RC15PurchasePredTop20.png "RC15")

![RetailrocketTop20](results/RetailrocketPurchasePredTop20.png "Retailrocket")

## Paper Results

![RRBaselines](results/RRBaselinesPurchasePredTop20.png "RR20")
![RRBaselines](results/RRBaselinesPurchasePredTop5.png "RR5")

## Citation

```
@misc{mozifian2023robust,
title={Robust Reinforcement Learning Objectives for Sequential Recommender Systems},
author={Melissa Mozifian and Tristan Sylvain and Dave Evans and Lili Meng},
year={2023},
eprint={2305.18820},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```