IEEE Big Data Cup 2024 Report: Predicting Chess Puzzle Difficulty at KnowledgePit.ai
We summarize the results of the IEEE BigData 2024 Cup: Predicting Chess Puzzle Difficulty – a data science competition organized at the knowledgepit.ai platform in association with the IEEE BigData 2024 conference. We describe the competition goal and tie it to existing research on human-computer interaction, focusing on task difficulty estimation and aligning human and AI behavior. We explain how we acquired and processed the data, separately for training and testing datasets. We review submitted solutions and evaluate their performance by comparing them to a simple benchmark. We explain how the achieved rating differences translate to user experience when solving chess puzzles. We further explore the concept of chess puzzle difficulty by replicating competition results with puzzle ratings obtained using chess bots only. We conclude with a summary of our findings and directions for future studies, as well as an invitation to the next edition of the competition in 2025.
Authors
- Andrzej Janusz (ORCID: https://orcid.org/0000-0002-9763-1399)
- Dominik Ślȩzak (ORCID: https://orcid.org/0000-0003-2453-4974)
- Maciej Świechowski (ORCID: https://orcid.org/0000-0002-8941-3199)
- Sebastian Stawicki (ORCID: https://orcid.org/0000-0002-6303-3884)
- Jan Zyśko
- Katarzyna Jagieła
Institutions
- University of Warsaw (PL)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/bigdata62323.2024.10825289
- Citations
- 18
- Primary Topic
- Sports Analytics and Performance
- Type
- article
- Field-Weighted Citation Impact
- 20.33