论文标题
社会机器人导航方法的分析：CNN编码器和增量学习作为深度强化学习的替代方案
Analysis of Social Robotic Navigation approaches: CNN Encoder and Incremental Learning as an alternative to Deep Reinforcement Learning
论文作者
论文摘要
在机器人场景中处理社会任务很困难，因为在学习循环中让人类与大多数最先进的机器学习算法不相容。探索渐进学习模型，尤其是涉及强化学习的模型时，就是这种情况。在这项工作中，我们通过分析有关适应性卷积编码器的社会导航任务的先前研究来讨论此问题和可能的解决方案。
Dealing with social tasks in robotic scenarios is difficult, as having humans in the learning loop is incompatible with most of the state-of-the-art machine learning algorithms. This is the case when exploring Incremental learning models, in particular the ones involving reinforcement learning. In this work, we discuss this problem and possible solutions by analysing a previous study on adaptive convolutional encoders for a social navigation task.
