Unifying temporal and organizational scales in multiscale decision-making
Unifying temporal and organizational scales in multiscale decision-making
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统一多尺度决策中的时间和组织尺度
DOI：
10.1016/j.ejor.2012.06.038
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
A. Deshmukh
中科院分区：
文献类型：
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作者：
Christian Wernz;A. Deshmukh
在企业系统中，决策对于组织层级的所有级别的代理来说是一项复杂的任务。为了计算最优行动方案，智能体必须包括不确定性和其他智能体的预期决策，认识到它们也参与随机的博弈论推理过程。此外，更高级别的代理人寻求通过提供激励来调整其下属的利益。激励给予者和接受者需要在最优策略计算中考虑激励对他们收益的影响。在本文中，我们提出了一个多尺度的决策模型，占随着时间的推移的不确定性和组织的相互依赖性。多尺度决策将随机博弈与层次马尔可夫决策过程相结合，以建模和解决多组织尺度和多时间尺度问题。这是第一个统一了组织和时间尺度的模型，可以解决3-agent，3-period问题。解可以用低计算量的解析方程导出。我们将该模型应用于一个服务企业的挑战，说明了该模型的适用性和相关性。本文对多尺度决策理论的建立做出了重要贡献，并代表了解决一般X-agent，T-period问题的关键一步。
In enterprise systems, making decisions is a complex task for agents at all levels of the organizational hierarchy. To calculate an optimal course of action, an agent has to include uncertainties and the anticipated decisions of other agents, recognizing that they also engage in a stochastic, game-theoretic reasoning process. Furthermore, higher-level agents seek to align the interests of their subordinates by providing incentives. Incentive-giving and receiving agents need to include the effect of the incentive on their payoffs in the optimal strategy calculations. In this paper, we present a multiscale decision-making model that accounts for uncertainties and organizational interdependencies over time. Multiscale decision-making combines stochastic games with hierarchical Markov decision processes to model and solve multi-organizational-scale and multi-time-scale problems. This is the first model that unifies the organizational and temporal scales and can solve a 3-agent, 3-period problem. Solutions can be derived as analytic equations with low computational effort. We apply the model to a service enterprise challenge that illustrates the applicability and relevance of the model. This paper makes an important contribution to the foundation of multiscale decision theory and represents a key step towards solving the general X-agent, T-period problem.