不完全已知任务环境下协调的自适应

F. Wall
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引用次数: 1

摘要

负责完成系统任务的多个主体之间的协调是组织设计的基本问题之一。本文研究了在任务复杂性不完全已知的情况下,如系统经历外部冲击时,系统会出现哪种协调模式。为此,采用了基于NK适应度景观的基于agent的仿真。仿真模型对不同级别的任务复杂性和不同程度的任务知识进行控制。研究结果为以下假设提供了广泛的支持:当需要合作完成的任务的复杂性很高时,就会出现强烈的协调。此外,研究结果表明,任务知识的准确性可能会微妙地影响协调模式的出现。
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Self-Adaptation of Coordination in Imperfectly Known Task Environments
The coordination of multiple agents which are collectively responsible for accomplishing a system's task is among the fundamental issues of organizational design. This paper studies which mode of coordination emerges in systems when the task complexity is imperfectly known, for example, as the system has gone through an external shock. For this, an agent-based simulation based on NK fitness landscapes is employed. The simulation model controls for different levels of task complexity and different degrees of knowledge about the task. The results provide broad support for the conjecture that intense coordination emerges when the complexity of the task to be accomplished collaboratively is high. Moreover, the results suggest that the precision of knowledge about the task subtly may affect which coordination mode emerges.
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