A mechanism for value-sensitive decision-making.
A mechanism for value-sensitive decision-making.
复制标题
价值敏感决策的机制。
DOI：
10.1371/journal.pone.0073216
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Marshall JA
中科院分区：
文献类型：
--
作者：
Pais D;Hogan PM;Schlegel T;Franks NR;Leonard NE;Marshall JA
我们对受寻屋蜂群集体选择启发的决策机制进行了动力系统分析，揭示了交叉抑制“停止信号”在提高决策能力中的关键作用。我们表明，交叉抑制的强度是一个决策参数，影响决策如何依赖于价值差异和替代方案的平均值；这与许多以前的决策机制模型形成鲜明对比，这些模型通常对决策准确性而不是所选选项的价值敏感。交叉抑制的强度决定了价值相似的替代品的僵局何时维持或打破，作为平均值的函数；因此，交叉抑制强度的变化允许自适应的时间依赖性决策策略。交叉抑制还调整了可靠区分所需的替代方案之间的最小差异，其方式类似于韦伯可见差异定律。最后，当替代方案的值差异足够大以至于产生影响时，交叉抑制会调整实现的速度与准确性的权衡。我们认为该模型以及替代方案值的重要作用可以描述其他决策系统，包括细胞内调节回路和简单的神经回路，并且可以为人工系统的决策算法设计提供指导，特别是那些没有集中控制的系统。
We present a dynamical systems analysis of a decision-making mechanism inspired by collective choice in house-hunting honeybee swarms, revealing the crucial role of cross-inhibitory ‘stop-signalling’ in improving the decision-making capabilities. We show that strength of cross-inhibition is a decision-parameter influencing how decisions depend both on the difference in value and on the mean value of the alternatives; this is in contrast to many previous mechanistic models of decision-making, which are typically sensitive to decision accuracy rather than the value of the option chosen. The strength of cross-inhibition determines when deadlock over similarly valued alternatives is maintained or broken, as a function of the mean value; thus, changes in cross-inhibition strength allow adaptive time-dependent decision-making strategies. Cross-inhibition also tunes the minimum difference between alternatives required for reliable discrimination, in a manner similar to Weber's law of just-noticeable difference. Finally, cross-inhibition tunes the speed-accuracy trade-off realised when differences in the values of the alternatives are sufficiently large to matter. We propose that the model, and the significant role of the values of the alternatives, may describe other decision-making systems, including intracellular regulatory circuits, and simple neural circuits, and may provide guidance in the design of decision-making algorithms for artificial systems, particularly those functioning without centralised control.
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影响因子：
25
作者：
Krajbich, Ian;Armel, Carrie;Rangel, Antonio
通讯作者：
Rangel, Antonio
DOI：
10.1098/rspb.2002.2001
发表时间：
2002-07-07
影响因子：
4.7
作者：
Britton, NF;Franks, NR;Seeley, TD
通讯作者：
Seeley, TD
DOI：
10.1073/pnas.0604801103
发表时间：
2006-10-24
影响因子：
11.1
作者：
Pratt, Stephen C.;Sumpter, David J. T.
通讯作者：
Sumpter, David J. T.
影响因子：
2.3
作者：
Passino, Kevin M.;Seeley, Thomas D.;Visscher, P. Kirk
通讯作者：
Visscher, P. Kirk
影响因子：
25
作者：
Kim, JN;Shadlen, MN
通讯作者：
Shadlen, MN