Optimal Common Contract with Heterogeneous Agents

Optimal Common Contract with Heterogeneous Agents
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异构代理的最优公共合约

DOI:
10.1609/aaai.v34i05.6224
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发表时间:
2019
期刊:
ArXiv
影响因子:
--
通讯作者:
Xiwang Yang
Xiwang Yang
中科院分区:
--
文献类型:
--
作者:
Shenke Xiao;Zihe Wang;Mengjing Chen;Pingzhong Tang;Xiwang Yang

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本文研究了具有异质代理人的委托代理问题。以往的研究假设委托人与每个代理人签订独立的激励合同,使他们在任务上投入更多的努力。然而,在许多情况下,为了公平起见,这些合同需要完全相同。研究了最优公共合同问题。据我们所知,这是第一次尝试考虑这一自然和重要的概括。我们首先证明这个问题是NP完全的。然后,我们提供了一个动态规划算法来计算$O(n^2m)$时间内的最优合同,其中$n,m$是代理和动作的数量,假设代理的成本函数服从递增差性质。最后,我们推广了设置,使得每个代理可以选择直接在$[0,1]$中产生奖励。我们提供了一个$O(\log n)$-近似算法的推广。
We consider the principal-agent problem with heterogeneous agents. Previous works assume that the principal signs independent incentive contracts with every agent to make them invest more efforts on the tasks. However, in many circumstances, these contracts need to be identical for the sake of fairness. We investigate the optimal common contract problem. To our knowledge, this is the first attempt to consider this natural and important generalization. We first show this problem is NP-complete. Then we provide a dynamic programming algorithm to compute the optimal contract in $O(n^2m)$ time, where $n,m$ are the number of agents and actions, under the assumption that the agents' cost functions obey increasing difference property. At last, we generalize the setting such that each agent can choose to directly produce a reward in $[0,1]$. We provide an $O(\log n)$-approximate algorithm for this generalization.
委托搜索近似于高效搜索
DOI: 10.1145/3219166.3219205
发表时间: 2018
期刊: Proceedings of the 2018 ACM Conference on Economics and Computation
影响因子: --
作者:
Kleinberg, Jon;Kleinberg, Robert
通讯作者: Kleinberg, Robert
多智能体评估机制
DOI: --
发表时间: 2020
期刊: AAAI
影响因子: --
作者:
Alon, T.;Dobson, M.;Procaccia, A.;Talgam-Cohen, I;Tucker-Foltz, J.
通讯作者: Tucker-Foltz, J.