--- dataset_info: features: - name: starting sequence: int64 - name: target dtype: int64 - name: closest dtype: int64 - name: expression dtype: string - name: delta dtype: int64 - name: score dtype: int64 - name: size dtype: int64 splits: - name: train num_bytes: 545707980 num_examples: 4799618 - name: test num_bytes: 136431391 num_examples: 1199904 download_size: 188317202 dataset_size: 682139371 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* license: mit tags: - countdown - math - reasoning pretty_name: Countdown Numbers Game (random puzzles with non-zero max scores, sizes 3–8) size_categories: - 1M | **Dataset Variant** | **Dataset Name** | **Download** | | ------------------- | -------------------------- | --------------------------------------------------------------------------------------- | | Random | `countdown-numbers-3-8` | [🤗 HuggingFace](https://huggingface.co/datasets/alexjackson17/countdown-numbers-3-8) | | Random Solvable | `countdown-numbers-3-8-nz` | [🤗 HuggingFace](https://huggingface.co/datasets/alexjackson17/countdown-numbers-3-8-nz) | | Coundown Game Rules | `countdown-numbers-6-gr` | [🤗 HuggingFace](https://huggingface.co/datasets/alexjackson17/countdown-numbers-6-gr) | --- ## Dataset Overview Each data point in the dataset includes: - **Numbers:** A sequence of $n$ integers $s_1, s_2, \ldots, s_n$ where $s_i \in \{1, 2, \ldots, 100\}$ for all $i \in \{1, 2, \ldots, n\}$, and $n \in \{3, 4, \ldots, 8\}$. (Note: In the traditional Countdown game, the numbers are subject to more specific restrictions.) - **Target:** An integer $t \in \{1, 2, \ldots, 999\}$. (For context, the standard Countdown game usually features targets from 101 and above.) - **Closest:** The value computed by a solver $r \in \{1, 2, \ldots, 999\}$ that is closest to the target number. - **Expression:** The arithmetic expression used to compute the closest value. For instance, $((2 + 48) \times 5) \div 10$ - **Delta:** The absolute difference between the target and the closest value, i.e. $|t - r|$. - **Score:** The Countdown score calculated as $\max(0, 10 - |t - r|)$. This score reflects how close the computed value is to the target. --- ## Dataset Variants This dataset is provided in three variants: 1. **Random:** Configurations and solutions generated by uniformly sampling and solving one million game instances, without additional restrictions. 1. **Random Solvable (Score > 0):** Configurations are generated by uniformly sampling numbers and then **rejecting** any sample that results in an unsolvable instance (i.e., a score of 0). This variant ensures that each instance has a solution that yields a positive score. 1. **Countdown:** Configurations generated by sampling **6 numbers** in the style of the British TV show *Countdown*. ### Score Distributions The following histograms show the distribution of scores for each dataset variant: #### Random Variant #### Random Solvable (Score > 0) Variant #### Countdown Game Rules --- ## Generation Process The dataset was created by: - Uniformly sampling numbers within the specified ranges. - Solving each sampled instance to determine the closest value, the corresponding expression, the difference from the target, and the score. - For the **Random Solvable (Score > 0)** variant, rejection sampling was applied: instances that did not yield a positive score were discarded. The train and test splits were created by randomly partitioning the instances into 80% training and 20% testing, using a stratified split based on the score and number of starting values. ### Split Score/Size Distributions The final distributions of scores and numbers are shown in the following histograms: #### Random Variant #### Random Solvable (Score > 0) Variant #### Countdown Game Rules --- ## How to Use the Dataset You can load and use this dataset with the Hugging Face `datasets` library. For example: ```python from datasets import load_dataset dataset = load_dataset("alexjackson17/countdown-numbers-6-gr") # Example: Access the first entry in the training split example = dataset["train"][0] print("Numbers: ", example["starting"]) print("Target: ", example["target"]) print("Closest: ", example["closest"]) print("Expression: ", example["expression"]) print("Difference: ", example["delta"]) print("Score: ", example["score"]) ``` --- ## Citation If you use this dataset in your research or projects, please cite it as follows: ```bibtex @misc{jackson2025countdown, title = {Countdown Numbers Game Dataset}, author = {Alex Jackson}, year = {2025}, note = {Released under the MIT License}, } ``` --- ## Funding Attribution This work was supported by UK Research and Innovation [grant number EP/S023356/1], in the UKRI Centre for Doctoral Training in Safe and Trusted Artificial Intelligence ([www.safeandtrustedai.org](https://www.safeandtrustedai.org)). --- ## License This dataset is released under the MIT License. See the [LICENSE](LICENSE) file for more information. For questions, feedback, or further information, please contact [Alex Jackson](mailto:mail@alexjackson.uk).