约束下的行动选择:机器和人类行为的动态优化

R. Kozma, D. Harter, S. Achunala
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引用次数: 3

摘要

生物大脑有能力适应行为,以维持在面对日益困难的限制任务中的表现。我们提出了一个具有不同资源和时间约束条件的任务。我们将启发式和神经网络模型与人类数据进行比较,并推测行动选择的动态机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Action selection under constraints: dynamic optimization of behavior in machines and humans
Biological brains are capable of adaptive behavior to sustain performance in tasks in the face of increasingly difficult constraints.. We present a task with varying conditions of resource and time constraints. We compare our heuristic and neural network models to human data and speculate about dynamic mechanisms of action selection.
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