User:IssaRice/Aumann's agreement theorem: Difference between revisions

From Machinelearning
No edit summary
No edit summary
Line 1: Line 1:
Hal Finney's example
 
 
==Information partitions==
 
==Join and meet==
 
==Common knowledge==
 
==Statement of theorem==
 
==Hal Finney's example==


<math>\begin{array}{c|rrrrrr}
<math>\begin{array}{c|rrrrrr}
Line 44: Line 54:


Agent 1 knows he rolled a 2 and agent 2 rolled something between 1 and 3. Now, consider that agent 1 is additionally told that agent 2 did ''not'' roll a 1. Now agent 1's posterior probability of the event <math>X = 4</math> is 1/2. How does this affect the agreement theorem? It seems like agent 1's information partition changes...
Agent 1 knows he rolled a 2 and agent 2 rolled something between 1 and 3. Now, consider that agent 1 is additionally told that agent 2 did ''not'' roll a 1. Now agent 1's posterior probability of the event <math>X = 4</math> is 1/2. How does this affect the agreement theorem? It seems like agent 1's information partition changes...
==Aumann's coin flip example==


<ref>Tyrrell McAllister. [https://web.archive.org/web/20110725162431/http://dl.dropbox.com/u/34639481/Aumann_agreement_theorem.pdf "Aumann's agreement theorem"]. July 7, 2011.</ref>
<ref>Tyrrell McAllister. [https://web.archive.org/web/20110725162431/http://dl.dropbox.com/u/34639481/Aumann_agreement_theorem.pdf "Aumann's agreement theorem"]. July 7, 2011.</ref>

Revision as of 23:39, 24 August 2018


Information partitions

Join and meet

Common knowledge

Statement of theorem

Hal Finney's example

123456123456723456783456789456789105678910116789101112

1 2 3 4 5 6
1
2

E={ω∈Ω:Pr(A∣I(ω))=q1 and Pr(A∣J(ω))=q2}

One of the assumptions in the agreement theorem is that E is common knowledge. This seems like a pretty strange requirement, since it seems like the posterior probability of A can never change no matter what else the agents condition on in addition to E. For example, what if we bring in agent 3 and make the posteriors common knowledge again?

What if we take E′={ω∈Ω:Pr(A∣I(ω))=q1} and say that agent 1 knows E′?

In the form of E above, we can change A to be any subset of Ω and q1,q2 to be any numbers in [0,1]. We can also set the state of the world to be any ω∈Ω. The agreement theorem says that as we vary these parameters, if we ever find that (I∧J)(ω)⊂E, then we must have q1=q2.

Define X((x,y))=x+y.

ω A q1 q2 Explanation
(2, 3) 2≤X≤6 1 1 Given these parameters, E=(I∧J)(ω) so E is common knowledge. This satisfies the requirement of the agreement theorem, and indeed 1=1.
(2, 3) X=4 1/3 1/3 Given these parameters, E=(I∧J)(ω) so E is common knowledge. This satisfies the requirement of the agreement theorem, and indeed 1/3=1/3.
(2, 3) X=4 1/3 1/3 Given these parameters, E={2,3}×{2,3}, which is not a superset of (I∧J)(ω), so E is not common knowledge. Nonetheless, 1/3=1/3. (Is this a case of mutual knowledge that is not common knowledge?)

Agent 1 knows he rolled a 2 and agent 2 rolled something between 1 and 3. Now, consider that agent 1 is additionally told that agent 2 did not roll a 1. Now agent 1's posterior probability of the event X=4 is 1/2. How does this affect the agreement theorem? It seems like agent 1's information partition changes...

Aumann's coin flip example

[1]

[2]

[3]

[4]

[5]

References