Game theory challenge Can you predict human behavior Lucas Husted

A few months ago we posed a challenge
to our community.

We asked everyone: given a range of
integers from 0 to 100,

guess the whole number closest to 2/3
of the average of all numbers guessed.

So if the average of all guesses is 60,
the correct guess will be 40.

What number do you think was the
correct guess at 2/3 of the average?

Let’s see if we can try and reason
our way to the answer.

This game is played under conditions known
to game theorists as common knowledge.

Not only does every player have
the same information —

they also know that everyone else does,

and that everyone else knows that
everyone else does, and so on, infinitely.

Now, the highest possible average would
occur if every person guessed 100.

In that case, 2/3 of the average
would be 66.66.

Since everyone can figure this out,

it wouldn’t make sense to guess
anything higher than 67.

If everyone playing comes to
this same conclusion,

no one will guess higher than 67.

Now 67 is the new highest
possible average,

so no reasonable guess should be
higher than ⅔ of that, which is 44.

This logic can be extended further
and further.

With each step, the highest possible
logical answer keeps getting smaller.

So it would seem sensible to guess the
lowest number possible.

And indeed, if everyone chose zero,

the game would reach what’s known
as a Nash Equilibrium.

This is a state where every player has
chosen the best possible strategy

for themselves given
everyone else playing,

and no individual player can benefit
by choosing differently.

But, that’s not what happens
in the real world.

People, as it turns out, either aren’t
perfectly rational,

or don’t expect each other
to be perfectly rational.

Or, perhaps, it’s some combination
of the two.

When this game is played in
real-world settings,

the average tends to be somewhere
between 20 and 35.

Danish newspaper Politiken ran the game
with over 19,000 readers participating,

resulting in an average of roughly 22,
making the correct answer 14.

For our audience, the average was 31.3.

So if you guessed 21 as 2/3 of
the average, well done.

Economic game theorists have a
way of modeling this interplay

between rationality and practicality
called k-level reasoning.

K stands for the number of times a
cycle of reasoning is repeated.

A person playing at k-level 0 would
approach our game naively,

guessing a number at random without
thinking about the other players.

At k-level 1, a player would assume
everyone else was playing at level 0,

resulting in an average of 50,
and thus guess 33.

At k-level 2, they’d assume that everyone
else was playing at level 1,

leading them to guess 22.

It would take 12 k-levels to reach 0.

The evidence suggests that most
people stop at 1 or 2 k-levels.

And that’s useful to know,

because k-level thinking comes into
play in high-stakes situations.

For example, stock traders evaluate stocks
not only based on earnings reports,

but also on the value that others
place on those numbers.

And during penalty kicks in soccer,

both the shooter and the goalie decide
whether to go right or left

based on what they think the other
person is thinking.

Goalies often memorize the patterns of
their opponents ahead of time,

but penalty shooters know that
and can plan accordingly.

In each case, participants must weigh
their own understanding

of the best course of action against how
well they think other participants

understand the situation.

But 1 or 2 k-levels is by no means
a hard and fast rule—

simply being conscious of this tendency
can make people adjust their expectations.

For instance, what would happen
if people played the 2/3 game

after understanding the difference between
the most logical approach

and the most common?

Submit your own guess at what 2/3
of the new average will be

by using the form below,

and we’ll find out.

几个月前,我们对社区提出了
挑战。

我们问大家:给定一个
从 0 到 100

的整数范围,猜测最接近
所有猜测数字平均值 2/3 的整数。

所以如果所有猜测的平均值是 60,
那么正确的猜测将是 40。

你认为
在平均值的 2/3 处正确猜测的数字是多少?

让我们看看我们是否可以尝试并推理
出答案。

这个游戏是在
博弈论者已知为常识的条件下进行的。

不仅每个玩家都
拥有相同的信息——

他们还知道其他

人都知道,而且其他人都知道
其他人也知道,等等,无穷无尽。

现在,
如果每个人都猜到 100,就会出现可能的最高平均值。

在这种情况下,平均值的 2/3
将是 66.66。

既然每个人都可以

猜到,那么猜测
高于 67 的任何东西都是没有意义的。

如果每个人都
得出同样的结论,那么

没有人会猜测高于 67。

现在 67 是新的最高
可能平均值,

所以没有合理的猜测 应该
高于 2/3,即 44。

这个逻辑可以进一步扩展

随着每一步,最高可能的
逻辑答案越来越小。

因此,猜测可能的最低数字似乎是明智的

事实上,如果每个人都选择零

,游戏将达到
所谓的纳什均衡。

在这种状态下,每个玩家都为自己
选择了最好的策略

,而
其他人都在玩

,没有一个玩家可以
通过不同的选择而受益。

但是,这不是
现实世界中发生的事情。

事实证明,人们要么不是
完全理性的,

要么不期望
彼此是完全理性的。

或者,也许,它是两者的某种组合

当这个游戏在
现实世界中玩时

,平均数往往
在 20 到 35 之间。

丹麦报纸 Politiken 运行该游戏时
有超过 19,000 名读者参与,

平均结果约为 22
,正确答案为 14。

对于我们的 观众,平均为31.3。

因此,如果您猜 21
是平均值的 2/3,那就太好了。

经济博弈论者有一种
方法来模拟

理性和实用性之间的这种相互作用,
称为 k 级推理。

K
代表推理循环重复的次数。

一个在 k-level 0 玩的人会
天真地接近我们的游戏,

随机猜测一个数字而不
考虑其他玩家。

在 k-level 1,玩家会假设
其他人都在玩 level 0,

因此平均为 50
,因此猜测为 33。

在 k-level 2,他们会假设
其他人都在玩 level 1,

领先 他们猜测

22。达到 0 需要 12 k-levels

。证据表明,大多数
人停在 1 或 2 k-levels。

知道这一点很有用,

因为 k 级思维
在高风险情况下发挥作用。

例如,股票交易员
不仅根据收益报告评估股票,

还根据其他
人对这些数字的评价。

在足球的点球大战中

,射手和守门员都

根据他们认为
对方的想法决定是向右还是向左。

守门员通常会提前记住对手的模式

但点球手知道这一点
并可以做出相应的计划。

在每种情况下,参与者都必须权衡
他们自己

对最佳行动方案的
理解与他们认为其他参与者

对情况的理解程度。

但是 1 或 2 k-levels 绝不是
一个硬性规定——

只要意识到这种趋势
就可以让人们调整他们的期望。

例如,如果人们

在理解
了最合乎逻辑的方法

和最常见的方法之间的区别后玩 2/3 游戏会发生什么? 使用下面的表格

提交您
对新平均值的 2/3 的猜测

,我们会找出答案。