<p>According to <a href="https://en.wikipedia.org/wiki/Extensive-form_game" rel="nofollow noreferrer">Wikipedia</a>, an incomplete-information game can be converted into an imperfect-information game with complete information in extensive form by using the so-called Harsanyi transformation, which means adding chance nodes at the beginning of the game:</p>
<blockquote>
<p>It may be the case that a player does not know exactly what the
payoffs of the game are or of what type their opponents are. This sort
of game has incomplete information. In extensive form, it is
represented as a game with complete but imperfect information using
the so-called Harsanyi transformation.</p>
</blockquote>
<p>My question is: is this transformation feasible only for some kind of incomplete-information games or for all of them? I easily see how it can be done when the distributions of probabilities over the possible types of players are known. In this case, you add one or more chance nodes at the beginning of the game, labeled with said probabilities. But what if the distributions are not known? Can the transformation be made? In this case, I suppose the chance nodes added would not be labeled. Would this still be an imperfect but complete-information game? Would it still be an extensive-form game at all, considering that in the definition of the extensive-form game given by Wikipedia the probabilities of actions by nature (chance nodes) are known?</p>
<p>If the answer to this question is &quot;only certain kinds of incomplete-information games can be converted in imperfect but complete-information games&quot;, then another question naturally rises: considering that there is no difference in modeling an imperfect-information game and some particular kinds of incomplete-information games, are imperfect-information games a subset of incomplete-information games?</p>
<p>If the answer is &quot;all the incomplete-information games can be converted in imperfect but complete-information games&quot;, then I would ask if imperfect-information games are exactly all of the games with incomplete-information.</p>

CC BY-SA 4.0
2020-06-23T17:37:46.537Z
How do you define games of incomplete information? I'm not sure I understand what you mean by " if the distributions are not known."
Michael Greinecker
CC BY-SA 4.0
2020-06-24T12:09:53.380Z
How to define incomplete-information games is part of my question... it is not entirely clear to me. By "distributions" I mean the probability distributions over the possible types of players, which translate to different probability labels on the edges of chance nodes. The type of a player is his own function from outcomes to utilities, which in incomplete-information games (according to all the definitions of incomplete-information game I've seen) is not known with certainty.
Mark Smith
CC BY-SA 4.0
2020-06-24T12:12:13.837Z
I think in that case, it might be better to look in textbooks; the topic is a bit broad.
Michael Greinecker
<game-theory>
Are imperfect-information games in extensive form exactly the same as sequential incomplete-information games?
Mark Smith
# Are imperfect-information games in extensive form exactly the same as sequential incomplete-information games?

(Asked by: username_0 on 2020-06-23)

According to [Wikipedia](https://en.wikipedia.org/wiki/Extensive-form_game), an incomplete-information game can be converted into an imperfect-information game with complete information in extensive form by using the so-called Harsanyi transformation, which means adding chance nodes at the beginning of the game:

> It may be the case that a player does not know exactly what the
> payoffs of the game are or of what type their opponents are. This sort
> of game has incomplete information. In extensive form, it is
> represented as a game with complete but imperfect information using
> the so-called Harsanyi transformation.

My question is: is this transformation feasible only for some kind of incomplete-information games or for all of them? I easily see how it can be done when the distributions of probabilities over the possible types of players are known. In this case, you add one or more chance nodes at the beginning of the game, labeled with said probabilities. But what if the distributions are not known? Can the transformation be made? In this case, I suppose the chance nodes added would not be labeled. Would this still be an imperfect but complete-information game? Would it still be an extensive-form game at all, considering that in the definition of the extensive-form game given by Wikipedia the probabilities of actions by nature (chance nodes) are known?

If the answer to this question is "only certain kinds of incomplete-information games can be converted in imperfect but complete-information games", then another question naturally rises: considering that there is no difference in modeling an imperfect-information game and some particular kinds of incomplete-information games, are imperfect-information games a subset of incomplete-information games?

If the answer is "all the incomplete-information games can be converted in imperfect but complete-information games", then I would ask if imperfect-information games are exactly all of the games with incomplete-information.

**Tags:** game-theory

> **Comments:**
> **username_1**: How do you define games of incomplete information? I'm not sure I understand what you mean by " if the distributions are not known."  
> **username_0**: How to define incomplete-information games is part of my question... it is not entirely clear to me. By "distributions" I mean the probability distributions over the possible types of players, which translate to different probability labels on the edges of chance nodes. The type of a player is his own function from outcomes to utilities, which in incomplete-information games (according to all the definitions of incomplete-information game I've seen) is not known with certainty.  
> **username_1**: I think in that case, it might be better to look in textbooks; the topic is a bit broad.  

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## 0 answers

