摘要
由一名新闻记者-机器人和机器学习的工作人员新闻编辑每日新闻-机器人和自动化的最新数据在一份新的报告中呈现。根据NewsRx编辑在德克萨斯州奥斯汀的新闻报道，研究表明：“模仿学习(IL)是一种很有前途的模式，可以通过演示教机器人执行新任务。大多数现有的智能学习方法都利用神经网络(NN)，然而，这些方法有几个众所周知的局限性：它们1需要大量的训练数据，2难以解释，3难以完善和适应。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Robotics - Robotics and Automation are presented in a new report. According to news reporting out of Austin, Texas, by NewsRx editors, research stated, “Imitation Learning (IL) is a promising paradigm for teaching robots to perform novel tasks using demonstrations . Most existing approaches for IL utilize neural networks (NN), however, these methods suffer from several wellknown limitations: they 1) require large amounts of training data, 2) are hard to interpret, and 3) are hard to refine and adapt .”
NETL
NSTL