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The road sign problem revisited: handling delayed response tasks with neural robot controllers

机译:Road标志问题重新审视:使用神经机器人控制器处理延迟响应任务

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The 'road sign problem' is a class of delayed response tasks in which an agent's correct turning direction at a T-j unction is dependent on a stimulus it has encountered earlier. Neural robot controllers of four different architectures have been evaluated in experiments with six different variations of the problem. The highest reliability was achieved by Extended Sequential Cascaded Networks, a higher-order recurrent neural network architecture.
机译:“道路标志问题”是一类延迟响应任务,其中T-J发作代理的正确转向方向取决于它之前遇到的刺激。在具有六种不同变化的实验中评估了四种不同架构的神经机器人控制器。通过扩展顺序级联网络实现最高可靠性,这是一个高阶复发性神经网络架构。

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