Game theory challenge: Can you predict human behavior? - Lucas Husted

1,569,131 views ・ 2019-11-05

TED-Ed


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翻译人员: Jiasi Hao 校对人员: 潘 可儿
00:06
A few months ago we posed a challenge to our community.
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几个月前,我们在自己的社群上 发起了一个挑战。
00:10
We asked everyone: given a range of integers from 0 to 100,
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我们问每个人: 从给定 0 到 100 的整数范围内,
00:15
guess the whole number closest to 2/3 of the average of all numbers guessed.
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猜测一个最接近 所有猜测数字平均数 2/3 的整数。
00:22
So if the average of all guesses is 60, the correct guess will be 40.
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即倘若所有猜测数的平均是 60, 那么正确的猜测将会是 40。
00:26
What number do you think was the correct guess at 2/3 of the average?
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你认为哪个数字会是 平均数 2/3 的正确猜测呢?
00:32
Let’s see if we can try and reason our way to the answer.
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让我们看看是否可以尝试并推理出 我们猜测答案的方法。
00:36
This game is played under conditions known to game theorists as common knowledge.
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这个博弈是在一先决条件下进行的, 该条件被博弈理论家称为常识。
00:41
Not only does every player have the same information —
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不仅每一个参与者 都有一样的信息储备——
00:44
they also know that everyone else does,
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他们也知道其他人都一样,
00:46
and that everyone else knows that everyone else does, and so on, infinitely.
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并且其他人也都知道 再其他人也如此,如此无限循环。
00:52
Now, the highest possible average would occur if every person guessed 100.
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现在,如果每个人都猜 100, 那最大的可能平均数将会出现。
00:58
In that case, 2/3 of the average would be 66.66.
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在那个情况下,平均数的 2/3 将会是 66.66。
01:03
Since everyone can figure this out,
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既然每个人可以明白这个道理,
01:05
it wouldn’t make sense to guess anything higher than 67.
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那就没有理由去猜比 67 大的整数。
01:09
If everyone playing comes to this same conclusion,
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如果每个人都在博弈中 得出同样的结论,
01:12
no one will guess higher than 67.
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没人会猜比 67 大的整数。
01:15
Now 67 is the new highest possible average,
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现在 67 是最大的可能平均数,
01:19
so no reasonable guess should be higher than ⅔ of that, which is 44.
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所以合理的猜测 就不应该比 67 的 2/3 大,即 44。
01:25
This logic can be extended further and further.
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这个逻辑可以不断地被拓展,
01:28
With each step, the highest possible logical answer keeps getting smaller.
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随着每一步,符合逻辑的 最大可能猜测数会不断变小。
01:33
So it would seem sensible to guess the lowest number possible.
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因此猜测最小的可能数字 看似非常明智。
01:38
And indeed, if everyone chose zero,
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确实,如果每个人都选择 0,
01:41
the game would reach what’s known as a Nash Equilibrium.
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这个博弈将会达到“纳什均衡”。
01:45
This is a state where every player has chosen the best possible strategy
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在这一情况中,
每个玩家在都为自己 选择了最优可能策略,
01:49
for themselves given everyone else playing,
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01:52
and no individual player can benefit by choosing differently.
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并且没有单独的玩家 可以通过不同选择受益。
01:57
But, that’s not what happens in the real world.
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但是这在现实世界不会发生。
02:01
People, as it turns out, either aren’t perfectly rational,
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事实证明, 人们要么不是完全理智的,
02:05
or don’t expect each other to be perfectly rational.
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要么不会预期别人能做到完全理智,
02:09
Or, perhaps, it’s some combination of the two.
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再或者可能是这两种情况的组合。
02:12
When this game is played in real-world settings,
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当这个博弈在真实世界中发生时,
02:15
the average tends to be somewhere between 20 and 35.
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平均数接近于 20 至 35 之间的某个整数。
02:20
Danish newspaper Politiken ran the game with over 19,000 readers participating,
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丹麦 Poolitiken 报纸曾开展这个博弈, 有超过 1.9 万读者参与。
02:26
resulting in an average of roughly 22, making the correct answer 14.
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其平均数结果约为 22, 使得最终正确答案为 14。
02:32
For our audience, the average was 31.3.
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而我们的观众参与者, 平均数为 31.3。
02:35
So if you guessed 21 as 2/3 of the average, well done.
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所以如果你的猜测数为 21, 那你猜得漂亮!
02:41
Economic game theorists have a way of modeling this interplay
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经济博弈理论家有一个 模拟理性和实践相互作用方法,
02:44
between rationality and practicality called k-level reasoning.
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称为“ k 级推理”。
02:49
K stands for the number of times a cycle of reasoning is repeated.
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其中 k 代表 一个推理周期的重复次数。
02:54
A person playing at k-level 0 would approach our game naively,
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一个 k 级为 0 的人 会非常天真地参与我们的博弈,
02:58
guessing a number at random without thinking about the other players.
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他不会考虑别人的选择 而只是任意地猜一个数字。
03:02
At k-level 1, a player would assume everyone else was playing at level 0,
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一个 k 级为 1 的人 会假设别人都在 0 级博弈,
03:07
resulting in an average of 50, and thus guess 33.
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进而平均数为 50, 因此猜测数为 33。
03:12
At k-level 2, they’d assume that everyone else was playing at level 1,
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一个 k 级为 2 的人 会假设其他人都在 1 级博弈,
03:17
leading them to guess 22.
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导致他们最终猜测数为 22。
03:19
It would take 12 k-levels to reach 0.
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这将要求 12 的 k 级 来达到猜测数为 0。
03:23
The evidence suggests that most people stop at 1 or 2 k-levels.
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事实证明大部分人 处于 1 或 2 的 k 级。
03:27
And that’s useful to know,
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而知道这一点很有用,
03:29
because k-level thinking comes into play in high-stakes situations.
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因为 k 级思维 在高风险情况下时常出现。
03:34
For example, stock traders evaluate stocks not only based on earnings reports,
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例如,股票交易员 不仅基于收益报告来评估股票,
03:39
but also on the value that others place on those numbers.
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也基于其他人 在那些数字上摆放的价值。
03:43
And during penalty kicks in soccer,
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在球赛的点球环节中,
03:45
both the shooter and the goalie decide whether to go right or left
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射门人和守门员 都凭借他们对彼此想法的预判
03:49
based on what they think the other person is thinking.
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来决定向右或向左跑。
03:52
Goalies often memorize the patterns of their opponents ahead of time,
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守门员时常提前 记住他们对手的习惯模式,
03:56
but penalty shooters know that and can plan accordingly.
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但罚球射手知道此事, 并依此做出相应计划。
04:00
In each case, participants must weigh their own understanding
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每个情况下,参与者必须衡量
自身对最优行为的理解,
04:03
of the best course of action against how well they think other participants
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来对抗他们认为 其他参与者对情况的了解深度。
04:07
understand the situation.
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04:10
But 1 or 2 k-levels is by no means a hard and fast rule—
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但是 1 或 2 的 k 级推理 绝不是硬性且速成的规定——
04:14
simply being conscious of this tendency can make people adjust their expectations.
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仅是人们对这种博弈趋势的意识 使人们调整他们的预期。
04:20
For instance, what would happen if people played the 2/3 game
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例如,当大家都了解了最符合逻辑的 与最普遍方法之间的区别,
04:24
after understanding the difference between the most logical approach
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再来玩这个 2/3 的博弈游戏,
04:28
and the most common?
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结果又会如何?
04:29
Submit your own guess at what 2/3 of the new average will be
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将你的新平均数 2/3 的猜测整数 填到以下表格并提交,
04:34
by using the form below,
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04:36
and we’ll find out.
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我们再来看看。
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