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          BBC Learning English 英語教學

          Vocabulary: games 詞匯: 游戲

          Hard games 難玩兒的游戲

          Is it possible to know what the opponent's next move will be?

          Do you think of yourself as a bit of an expert at board games like chess or Go?

          Maybe you're not quite as good as you think. New research from the University of Manchester and the University of Oxford suggests complex games like these are impossible to learn fully. They might even be too complex for the human mind to understand.

          Researchers studied two-player games, to try and understand the strategies which people use to make decisions during the game. Some games with two players are simple, with only a small number of possible moves. Noughts and crosses is like this. Players quickly work out the best strategy but that means the game soon becomes boring.

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          It gets more interesting when there are many possible moves. That's why people are so fascinated by complex games like chess, or the board game Go, or some card games. But what the researchers found was that with difficult games, players find it hard to work out the best strategy and their actions become less rational.

          This research is part of the field called game theory: the study of human strategic decision-making. Much thinking on how people play complex games is based on something called 'the equilibrium point', which is when players have a perfect knowledge of what they're doing and of what their opponents are doing.

          But complex games mean people don't have this perfect knowledge, and it can make their playing seem chaotic and hard to predict. When you add more than two players then of course the game becomes even harder to understand. Trading on the stock market is an example of a complex multi-player game – with important consequences for all of us.

          Economists base financial predictions of the stock market on equilibrium theory, assuming that traders are infinitely intelligent and rational. So the researchers at Manchester and Oxford believe their work can help us make better economic predictions in future.

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