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My-Custom-AI/ACE-BB

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 Dataset Description This dataset contains experimental data from studying how AI… See the full description on the dataset page: https://huggingface.co/datasets/My-Custom-AI/ACE-BB.

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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

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.

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 or contact the authors through the paper correspondence information.