README.md

---
dataset_info:
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- config_name: market_share
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  - name: experiment_label
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  - name: experiment_number
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  - name: desired_choice
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configs:
- config_name: choice_behavior
  data_files:
  - split: data
    path: choice_behavior/data-*
- config_name: market_share
  data_files:
  - split: data
    path: market_share/data-*
---
# ACE-BB Dataset

ACE-BB (Agentic e-Commerce - choice Behavior & Biases) is a set of experiments 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' choice behavior & biases.

## Paper

**ArXiv**: [https://arxiv.org/abs/XXXX.XXXXX](https://arxiv.org/abs/XXXX.XXXXX)

## Dataset Description

This dataset contains experimental data from studying how AI shopping agents behave in e-commerce settings:

### Choice Behavior & Biases Experiments
- 500 randomized scenarios per product category
- Exogenous variation in:
  - Product positions (2×4 grid layout)
  - Platform tags (Sponsored, Overall Pick, Scarcity)
  - Product attributes (price, rating, number of reviews)
- Measures AI agent sensitivity to platform levers and product characteristics

### Dataset Subsets

- `choice_behavior`
- `market_share`

## Usage

To reproduce experiments or run on new models, please refer to the [ACES codebase](https://github.com/mycustomai/ACE).

## Citation

If you use this dataset in your research, please cite:

```bibtex
@misc{allouah2025acebb,
	author       = { Amine Allouah, Omar Besbes, Josué D Figueroa, Yash Kanoria and Akshit Kumar },
	title        = { ACE-BB (Revision 499ec41) },
	year         = 2025,
	url          = { https://huggingface.co/datasets/My-Custom-AI/ACE-BB },
	doi          = { 10.57967/hf/6124 },
	publisher    = { Hugging Face }
}
```

## License

This dataset is licensed under the MIT License and includes publically accessible data from Amazon.com.

## Contact

For questions or issues, please open a GitHub issue in the [ACES repository](https://github.com/mycustomai/ACES) or contact the authors through the paper correspondence information.