Mastering Atari, Go, chess and shogi by planning with a learned model
نویسندگان
چکیده
منابع مشابه
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
The game of chess is the most widely-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. In contrast, the AlphaGo Zero program recently achieved superhuman performance in the ga...
متن کاملChess, Shogi, Go, Natural Developments in Game Research
In game programming research there are four interesting and related domains: chess, xiang qi (Chinese chess), shogi (Japanese chess) and go. In this article we will compare chess with shogi, both comparing the rules and the computational aspects of both games. We will see that chess and shogi are very similar, but that there are some important di erences that complicate game programming for sho...
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هدف از این تحقیق بررسی برخی عوامل ادراکی واحساسی یعنی استفاده از شیوه های یادگیری زبان ، انگیزه ها ونگرش نسبت به زبان انگلیسی در رابطه با زمینه زبانی زبان آموزان می باشد. هدف بررسی این نکته بود که آیا اختلافی چشمگیر میان زبان آموزان دو زبانه و تک زبانه در میزان استفاده از شیوه های یادگیری زبان ، انگیزه ها نگرش و سطح مهارت زبانی وجود دارد. همچنین سعی شد تا بهترین و موثرترین عوامل پیش بینی کننده ...
15 صفحه اولMastering the game of Go from scratch
In this report we pursue a transfer-learning inspired approach to learning to play the game of Go through pure self-play reinforcement learning. We train a policy network on a 5 ⇥ 5 Go board, and evaluate a mechanism for transferring this knowledge to a larger board size. Although our model did learn a few interesting strategies on the 5 ⇥ 5 board, it never achieved human level, and the transfe...
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ژورنال
عنوان ژورنال: Nature
سال: 2020
ISSN: 0028-0836,1476-4687
DOI: 10.1038/s41586-020-03051-4