關(guān)于博弈論的英文論文翻譯，里面包含原文。
英文題目：Learning and equilibrium as useful approximations: Accuracy of prediction on randomly selected constant sum games
作者：Ido Erev · Alvin E. Roth · Robert L. Slonim ·Greg Barron
（其中Roth為2012年諾貝爾經(jīng)濟學(xué)獎獲得者）
翻譯題目：學(xué)習(xí)模型和均衡模型作為有用的近似值：隨機選擇常數(shù)和博弈預(yù)測的精確性

中文摘要： 如果可以用充足的數(shù)據(jù)來拒絕一個理論值，但其結(jié)果可能是一個非常有用近似估計，實證者和理論家們在如何評估這類理論時會產(chǎn)生很多的誤解。一個標準化的實證設(shè)計報告指出了通過信息類的測試案例到底能否用來拒絕某種一般性理論。相比之下，本文詳述了一個有意義的實驗，旨在提出這個問題:“在平均水平下，一個理論所提供近似值達到什么標準才算好”。這樣重點集中在一類隨機選擇博弈當中,以及需要估計有多少對曾經(jīng)未經(jīng)查證的博弈數(shù)據(jù)實證對象要觀測。這樣做的實驗觀測結(jié)果比找一組新的博弈主體所得出的實證結(jié)果要更好一些。我們稱這個模型為等效觀測量,并探索其屬性。
關(guān)鍵字：學(xué)習(xí)模型；均衡模型；常數(shù)和博弈；等效觀測量ENO

英文再要：Abstract There is a good deal of miscommunication among experimenters and theorists about how to eva luate a theory that can be rejected by sufficient data, but may nevertheless be a useful approximation. A standard experimental design reports whether a general theory can be rejected on an informative test case. This paper, in contrast, reports an experiment designed to meaningfully pose the question:
“how good an approximation does a theory provide on average.” It focuses on a class of randomly selected games, and estimates how many pairs of experimental subjects would have to be observed playing a previously unexamined game before the mean of the experimental observations would provide a better prediction than
the theory about the behavior of a new pair of subjects playing this game. We call this quantity the model’s equivalent number of observations, and explore its properties.