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Zheng Li, Xinkai Chen, Jiaqing Fu, Ning Xie and Tingting Zhao
With the development of electronic game technology, the content of electronic games presents a larger number of units, richer unit attributes, more complex game mechanisms, and more diverse team strategies. Multi-agent deep reinforcement learning shines ...
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Yunlong Lu, Wenxin Li and Wenlong Li
Games have long been benchmarks and testbeds for AI research. In recent years, with the development of new algorithms and the boost in computational power, many popular games played by humans have been solved by AI systems. Mahjong is one of the most pop...
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Yunlong Lu and Wenxin Li
Games have long been benchmarks and test-beds for AI algorithms. With the development of AI techniques and the boost of computational power, modern game AI systems have achieved superhuman performance in many games played by humans. These games have vari...
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Ricky Sanjaya, Jun Wang and Yaodong Yang
In this paper, we quantify the non-transitivity in chess using human game data. Specifically, we perform non-transitivity quantification in two ways?Nash clustering and counting the number of rock?paper?scissor cycles?on over one billion matches from the...
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Charl Maree and Christian Omlin
The increased complexity of state-of-the-art reinforcement learning (RL) algorithms has resulted in an opacity that inhibits explainability and understanding. This has led to the development of several post hoc explainability methods that aim to extract ...
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Chen Chen, Feng Ma, Xiaobin Xu, Yuwang Chen and Jin Wang
Ships are special machineries with large inertias and relatively weak driving forces. Simulating the manual operations of manipulating ships with artificial intelligence (AI) and machine learning techniques becomes more and more common, in which avoiding...
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An important challenge for safety in machine learning and artificial intelligence systems is a set of related failures involving specification gaming, reward hacking, fragility to distributional shifts, and Goodhart’s or Campbell’s law. This ...
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