Agreeing to Disagree. STOR. Robert J. Aumann. The Annals of Statistics, Vol. 4, No. 6 (Nov., ), Stable URL. In “Agreeing to Disagree” Robert Aumann proves that a group of current probabilities are common knowledge must still agree, even if those. “Agreeing to Disagree,” R. Aumann (). Recently I was discussing with a fellow student mathematical ideas in social science which are 1).

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Unlike many questionable applications of theorems, this disafree-aumann appears to have been the intention of the paper itself, which itself cites a paper defending the application of such techniques to the real world. Business and economics portal Statistics portal Mathematics portal. Their posterior probabilities must then be the same. Studying the same issue from a different perspective, a research paper by Ziv Hellman considers what happens if priors are not common.

Retrieved from ” https: It may be worth noting that Yudkowsky has said he wouldn’t agree to try to reach an Aumann agreement with Hanson. However, Robin Hanson has presented an argument that Bayesians who agree about the processes that gave rise to their priors e.

Aumann’s agreement theorem

The Annals of Statistics. For concerns on copyright infringement please see: The Annals of Statistics 4 6 By using this site, you agree to the Terms of Use and Privacy Policy. Articles with short description. Essentially, the proof goes that if they were not, it would mean that they did not trust the accuracy of one another’s information, or did not disqgree-aumann the other’s computation, since a different probability being found by a rational agent is itself evidence of further evidence, and a rational agent should recognize this, and also recognize that one would, and that this would also be recognized, and so on.

Arrow’s impossibility theorem Aumann’s agreement theorem Folk theorem Minimax theorem Nash’s theorem Purification theorem Revelation principle Zermelo’s theorem. Both are given the same prior probability of the world being in a certain state, and separate sets of further information.


The one-sentence summary is “you can’t actually agree to disagree”: This theorem is almost agreeeing much a favorite of LessWrong as the “Sword of Bayes” [4] itself, because of its popular phrasing along the lines of “two agents acting rationally Both sets of information include the posterior probability arrived at by the other, as well as the fact that their prior probabilities are the same, the fact that the other knows its posterior probability, the set of events that might affect probability, the fact that the other knows these things, the fact that the other knows it knows these things, the fact that the other knows it knows the other knows it knows, ad infinitum this is “common knowledge”.

For such careful definitions of “perfectly disagree-aumxnn and “common knowledge” this is equivalent to saying that two functioning calculators will not give different answers on the same input. Views Read Edit Fossil record.

Scott Aaronson has shown that this is indeed the case. More specifically, if two people are genuine Bayesian rationalists with common priorsand if they each have common knowledge of their individual posterior probabilitiesthen their posteriors must be equal. Retrieved from ” https: Nash equilibrium Subgame perfection Mertens-stable equilibrium Bayesian Nash equilibrium Perfect Bayesian equilibrium Trembling hand Proper equilibrium Epsilon-equilibrium Correlated equilibrium Sequential equilibrium Quasi-perfect equilibrium Evolutionarily stable strategy Risk dominance Core Shapley value Pareto efficiency Gibbs equilibrium Quantal response equilibrium Self-confirming equilibrium Strong Nash equilibrium Markov perfect equilibrium.

This page was last modified on 12 Septemberat Theory and Decision 61 4 — Community Saloon bar To disagree-aumahn list What agfeeing going on?

Aumann’s agreement theorem – RationalWiki

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The paper presents a way to measure how distant priors are from being common. Aumann’s agreement theorem says that two people acting rationally in a certain precise sense and with common knowledge of each other’s beliefs cannot agree to disagree.


This page was last edited on 6 Octoberat Unless explicitly noted otherwise, all content licensed as indicated by RationalWiki: Scott Aaronson believes that Aumanns’s therorem can act as a corrective to overconfidence, and a guide as to what disagreements should look like. Or the paper’s own example, the fairness of a coin — such a simple example having been chosen for accessibility, it demonstrates the problem with applying such an oversimplified concept of information to real-world situations.

It was first formulated in the paper titled “Agreeing to Disagree” by Robert Aumannafter whom the theorem is named. A question arises whether such an agreement can be reached in a reasonable time and, from a mathematical perspective, whether this can be done efficiently.

Aumann : Agreeing to Disagree

From Wikipedia, the free encyclopedia. Thus, two rational Bayesian agents with the same priors and who know each other’s posteriors will agfeeing to agree.

Aumann’s agdeeing theorem [1] is the result of Robert Aumann’s, winner of the Swedish National Bank’s Prize in Economic Sciences in Memory of Alfred Nobelgroundbreaking discovery that a sufficiently respected game theorist can get anything into a peer-reviewed journal. Views Read Edit View history.

Yudkowsky ‘s mentor Robin Hanson tries to handwave this with disagree-aumnn about genetics and environment, [9] but to have sufficient common knowledge of genetics and environment for this to work practically would require a few calls to Laplace’s demon.

Simply knowing that another agent observed some information and came to their respective conclusion will force each to revise their beliefs, resulting eventually in total agreement on the correct posterior.

In game theoryAumann’s agreement theorem is a theorem which demonstrates that rational agents with common knowledge of each other’s beliefs cannot agree to disagree.

Scott Aaronson [3] sharpens this theorem by removing the common prior and limiting the number of messages communicated. Polemarchakis, We can’t disagree forever, Journal of Economic Theory 28′: Consider two agents tasked with performing Bayesian analysis this is “perfectly rational”.