Endgame Analysis of Dou Shou Qi
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Abstract (arXiv)
Dou Shou Qi is a game in which two players control a number of pieces, each of them aiming to move one of their pieces onto a given square. We implemented an engine for analyzing the game. Moreover, we created a series of endgame tablebases containing all configurations with up to four pieces. These tablebases are the first steps towards theoretically solving the game. Finally, we constructed decision trees based on the endgame tablebases. In this note we report on some interesting patterns.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Apr 2016.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 4; 2025: 2; 2026: 2.
11 papers.
- 2022TabLLM: Few-shot Classification of Tabular Data with Large Language Modelscited by 273
- 2024Privacy Preserving Prompt Engineering: A Surveycited by 24
- 2023A benchmark of categorical encoders for binary classificationcited by 5
- 2024IIFE: Interaction Information Based Automated Feature Engineeringcited by 4
- 2026FAMOSE: A ReAct Approach to Automated Feature Discoverycited by 4
- 2025JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMscited by 3
- 2024PaddingFlow: Improving Normalizing Flows with Padding-Dimensional Noisecited by 1
- 2024Federated Automated Feature Engineeringcited by 1
- 2025LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thoughtcited by 1
- 2026BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classificationcited by 1
- 2023Predictability of Machine Learning Algorithms and Related Feature Extraction Techniquescited by 0
- 2026BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification7 May 2026
- 2026FAMOSE: A ReAct Approach to Automated Feature Discovery19 Feb 2026
- 2025LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought21 May 2025
- 2025JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMs17 Feb 2025
- 2024Federated Automated Feature Engineering5 Dec 2024
- 2024IIFE: Interaction Information Based Automated Feature Engineering7 Sep 2024
- 2024Privacy Preserving Prompt Engineering: A Survey9 Apr 2024
- 2024PaddingFlow: Improving Normalizing Flows with Padding-Dimensional Noise13 Mar 2024
- 2023A benchmark of categorical encoders for binary classification17 Jul 2023
- 2023Predictability of Machine Learning Algorithms and Related Feature Extraction Techniques30 Apr 2023
- 2022TabLLM: Few-shot Classification of Tabular Data with Large Language Models19 Oct 2022