README.md

---
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    path: absolute_and_random_price/data-*
- config_name: instruction_following
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- config_name: rating
  data_files:
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- config_name: relative_price
  data_files:
  - split: data
    path: relative_price/data-*
license: mit
---
# ACE-RS Dataset

## Dataset Description

ACE-RS (Agentic e-CommercE - Rationality Suite) is a comprehensive dataset for studying how autonomous AI agents behave when shopping in e-commerce settings.
The dataset enables controlled experiments on AI shopping behavior by providing synthetic tasks which evaluate agents' economic rationality and basic instruction following.

## Paper

📄 **Paper**: [What is your AI Agent buying? Evaluation, Implications and Emerging Questions for Agentic e-Commerce](https://arxiv.org/abs/2508.02630)

## Dataset Subsets

The ACE-RS dataset contains multiple experimental subsets:

### 1. **Instruction Following**

- `instruction_following`:
  - Budget-constrained shopping tasks
  - Color-based product selection
  - Brand-specific requirements

### 2. **Rationality Tests**

- `absolute_and_random_price`
- `relative_price`
- `rating`

## Usage

For detailed instructions on how to use this dataset and run experiments, please refer to the [ACES codebase](https://github.com/mycustomai/ACES).

## Citation

If you use the ACERS dataset in your research, please cite:

```bibtex
@misc{allouah2025acers,
    author       = { Amine Allouah, Omar Besbes, Josué D Figueroa, Yash Kanoria and Akshit Kumar },
    title        = { ACE-RS (Revision bb94051) },
    year         = 2025,
    url          = { https://huggingface.co/datasets/My-Custom-AI/ACE-SR },
    doi          = { 10.57967/hf/6123 },
    publisher    = { Hugging Face }
}
```

## License

This dataset is licensed under the [MIT License](LICENSE) and includes data publically available from Amazon.com

## Links

- 💻 **Code Repository**: [https://github.com/mycustomai/ACES](https://github.com/mycustomai/ACES)
- 📊 **Dataset**: [HuggingFace Dataset Card](https://huggingface.co/datasets/My-Custom-AI/ACE-RS)
- 📄 **Paper** [Arxiv](https://arxiv.org/abs/2508.02630)