Difference between revisions of "Pareto efficiency"

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A set of decisions "x/y" (meaning that participant A chooses "x" while participant B chooses "y") is called Pareto optimal if there is '''no''' other state, other participants' concurrent actions and everybody's prior actions remaining the same, in which at least one participant can improve his own outcome.
 
A set of decisions "x/y" (meaning that participant A chooses "x" while participant B chooses "y") is called Pareto optimal if there is '''no''' other state, other participants' concurrent actions and everybody's prior actions remaining the same, in which at least one participant can improve his own outcome.
  
If a participant can improve his outcome, other participants' concurrent actions and everybody's prior actions remaining the same, the new decision set '''Pareto dominates''' the old set.  When there are no more decision sets that ''Pareto dominate'' the current set, the current set is said to be ''Pareto optimal''.
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If a participant can improve his outcome, other participants' concurrent actions and everybody's prior actions remaining the same, the new decision set '''Pareto dominates''' the old set.  When there are no more decision sets that ''Pareto dominate'' the current set, the current set is said to be '''Pareto optimal'''.
  
 
==An example - Prisoner's dilemna==
 
==An example - Prisoner's dilemna==

Revision as of 22:58, August 13, 2009

In game theory and economics, the concept of Pareto efficiency (or Pareto optimality) is a method to judge the efficiency of a set of decisions made by the participants. It was named after Vilfredo Pareto.

A set of decisions "x/y" (meaning that participant A chooses "x" while participant B chooses "y") is called Pareto optimal if there is no other state, other participants' concurrent actions and everybody's prior actions remaining the same, in which at least one participant can improve his own outcome.

If a participant can improve his outcome, other participants' concurrent actions and everybody's prior actions remaining the same, the new decision set Pareto dominates the old set. When there are no more decision sets that Pareto dominate the current set, the current set is said to be Pareto optimal.

An example - Prisoner's dilemna

B
not confess confess
A not confess A: good / B: good A: bad / B: very good
confess A: very good / B: bad A: OK / B: OK

In the one-stage game shown at the right side, prisoners A and B can concurrently choose between "not confess" and "confess". The result can either be "very good", "good", "OK", or "bad".

The highlighted field ("confess/confess") is the Pareto optimal situation. All other situations can be improved.

For example, in "not confess/confess" ("bad" for A, "very good" for B), A could switch to "confess". The result improves A's result to "OK" while changing B's result also to "OK". However now at "confess/confess", if B changes to "not confess", his result becomes "bad". Thus, "confess/confess" is Paretto optimal.

Generally in a game with finite steps, the efficient outcome may not necessarily be the outcome that maximizes aggregate utility and there may even exist an outcome that has greater utility for every participant. However, in a game with infinite steps, it can be shown that the efficient outcome does maximize aggregate utility.

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