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摘要翻譯：
在銷售信息產(chǎn)品時，銷售者可以提供一些免費的部分信息來改變?nèi)藗兊墓纼r，從而有可能增加整體收入。我們通過揭示部分信息來研究廣告信息產(chǎn)品的一般問題。我們考慮作為決策者的買家。決策問題的結(jié)果取決于買家不知道的世界狀態(tài)。買家可以做出自己的觀察，從而可以對世界的狀態(tài)持有不同的個人信仰。有一個信息賣家可以訪問世界的狀態(tài)。賣家可以通過透露部分信息來推廣信息。我們假設(shè)賣方選擇了一個長期的廣告策略，然后向它承諾。賣方的目標(biāo)是最大化預(yù)期收益。我們在兩個背景下研究這個問題。（1）賣方以某一類型的買方為目標(biāo)。在這種情況下，尋找最優(yōu)廣告策略相當(dāng)于尋找一個簡單函數(shù)的凹閉包。該函數(shù)是兩個量的乘積，即似然比和不確定性代價。在此基礎(chǔ)上，我們證明了最優(yōu)機構(gòu)的一些性質(zhì)，這些性質(zhì)允許我們用有限大小的凸程序求解最優(yōu)機構(gòu)。如果世界的狀態(tài)具有一定數(shù)量的可能實現(xiàn)，或者買方面臨具有一定數(shù)量的選擇的決策問題，那么凸規(guī)劃將具有多項式大小。對于一般問題，我們證明了尋找最優(yōu)機制是NP難的。（2）當(dāng)賣方面對不同類型的買方，并且只知道其類型的分布時，我們給出了一個近似算法，當(dāng)預(yù)測可能的買方類型不太困難時，我們將進(jìn)行購買。對于一般問題，我們證明了求常因子逼近是NP難的。
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英文標(biāo)題：
《Optimal Advertising for Information Products》
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作者：
Shuran Zheng and Yiling Chen
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最新提交年份：
2021
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分類信息：
一級分類：Computer Science 計算機科學(xué)
二級分類：Computer Science and Game Theory 計算機科學(xué)與博弈論
分類描述：Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
涵蓋計算機科學(xué)和博弈論交叉的所有理論和應(yīng)用方面，包括機制設(shè)計的工作，游戲中的學(xué)習(xí)（可能與學(xué)習(xí)重疊），游戲中的agent建模的基礎(chǔ)（可能與多agent系統(tǒng)重疊），非合作計算環(huán)境的協(xié)調(diào)、規(guī)范和形式化方法。該領(lǐng)域還涉及博弈論在電子商務(wù)等領(lǐng)域的應(yīng)用。
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一級分類：Economics 經(jīng)濟學(xué)
二級分類：Theoretical Economics 理論經(jīng)濟學(xué)
分類描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括對契約理論、決策理論、博弈論、一般均衡、增長、學(xué)習(xí)與進(jìn)化、宏觀經(jīng)濟學(xué)、市場與機制設(shè)計、社會選擇的理論貢獻(xiàn)。
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英文摘要：
When selling information products, the seller can provide some free partial information to change people's valuations so that the overall revenue can possibly be increased. We study the general problem of advertising information products by revealing partial information. We consider buyers who are decision-makers. The outcomes of the decision problems depend on the state of the world that is unknown to the buyers. The buyers can make their own observations and thus can hold different personal beliefs about the state of the world. There is an information seller who has access to the state of the world. The seller can promote the information by revealing some partial information. We assume that the seller chooses a long-term advertising strategy and then commits to it. The seller's goal is to maximize the expected revenue. We study the problem in two settings. (1) The seller targets buyers of a certain type. In this case, finding the optimal advertising strategy is equivalent to finding the concave closure of a simple function. The function is a product of two quantities, the likelihood ratio and the cost of uncertainty. Based on this observation, we prove some properties of the optimal mechanism, which allow us to solve for the optimal mechanism by a finite-size convex program. The convex program will have a polynomial-size if the state of the world has a constant number of possible realizations or the buyers face a decision problem with a constant number of options. For the general problem, we prove that it is NP-hard to find the optimal mechanism. (2) When the seller faces buyers of different types and only knows the distribution of their types, we provide an approximation algorithm when it is not too hard to predict the possible type of buyers who will make the purchase. For the general problem, we prove that it is NP-hard to find a constant-factor approximation.
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PDF鏈接：
https://arxiv.org/pdf/2002.10045
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