Where neuroscience and dynamic system theory meet autonomous robotics: A contracting basal ganglia model for action selection
Where neuroscience and dynamic system theory meet autonomous robotics: A contracting basal ganglia model for action selection
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DOI：
10.1016/j.neunet.2008.03.009
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发表时间：
2008-05-01
期刊：
影响因子：
7.8
通讯作者：
Slotine, J. -J.
中科院分区：
文献类型：
--
作者：
Girard, B.;Tabareau, N.;Slotine, J. -J.
行动选择，选择下一步做什么的问题，是任何自治代理架构的核心。我们在这里使用神经科学，动力系统理论和自主机器人的融合多学科的方法，以提出一个有效的行动选择机制的基础上的基底神经节的新模型。我们首先描述了关于局部投影动力系统的收缩理论的新发展。我们利用这些结果来设计一个稳定的计算模型的皮质-基底-丘脑-皮质回路。根据最近的解剖数据，我们包括通常被忽视的神经投射，参与执行准确的选择。最后，在一个标准的生存任务，该模型作为一个自主的机器人动作选择机制的效率进行评估。该模型表现出有价值的抖动避免和节能性能相比，一个简单的如果，然后，否则决策规则。(C)2008爱思唯尔有限公司保留所有权利。
Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, dynamical system theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction theory regarding locally projected dynamical systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule. (C) 2008 Elsevier Ltd. All rights reserved.