有限的理性决策网络与信念传播
Gerrit Schmid1, Sebastian Gottwald2, Daniel A Braun3
1Ulm University Institute of Neuroinformatics, 89081 Ulm, Germany gerrit.schmid@uni-ulm.de.
Neural computation
|October 9, 2024
概括
像大脑这样的复杂系统使用专门单位之间的局部通信. 这项研究表明,循环信息流和反循环可以改善有限理性网络中的决策性能.
科学领域:
- 计算神经科学是一种计算神经科学.
- 网络科学 网络科学
- 决策理论 决策理论
背景情况:
- 复杂的信息处理系统,类似于人类大脑,具有专门的,协作单位.
- 局部性,即在没有中央控制器的情况下在本地交换信息,是这些网络的关键特性.
研究的目的:
- 通过决策理论方法研究有界的理性决策者的网络.
- 探索循环信息处理路径和局部通信对系统性能的影响.
主要方法:
- 调整消息传递算法以促进本地信息流.
- 分析具有专业单位和循环通讯路径的网络.
- 检查具有有限理性的决策代理人.
主要成果:
- 循环信息处理和局部通信使循环依赖结构成为可能.
- 重复的通信可以提高有限的单元处理能力的系统的性能.
- 低于最佳的效用源于连接和反循环不足或过度的系统.
结论:
- 有界的理性代理网络从专业单位和局部循环通信中受益.
- 连接和反的程度对于优化复杂决策系统中的实用性至关重要.
- 消息传递算法可以适应用于通过反研究网络,从而推进对新兴智能的理解.
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