在线发现问题及其在终身强化学习中的应用The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning |
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课程网址: | http://videolectures.net/rldm2015_li_discovery_problem/ |
主讲教师: | Lihong Li |
开课单位: | 微软公司 |
开课时间: | 2015-07-28 |
课程语种: | 英语 |
中文简介: | 我们研究的是终身强化学习,即智能体从解决一系列任务中提取知识,以加速未来任务的学习。我们首先提出并研究了一个相关的在线发现问题,这个问题可以是独立的,并提出了一个上下界匹配的优化算法。然后将这些结果应用于创建一个具有形式化学习保证的健壮的、持续的终身强化学习算法,该算法适用于更广泛的场景,并在仿真中得到验证。 |
课程简介: | We study lifelong reinforcement learning where the agent extracts knowledge from solving a sequence of tasks to speed learning in future ones. We first formulate and study a related online discovery problem, which can be of independent interest, and propose an optimal algorithm with matching upper and lower bounds. These results are then applied to create a robust, continuous lifelong reinforcement learning algorithm with formal learning guarantees, applicable to a much wider scenarios, as verified in simulations. |
关 键 词: | 强化学习; 算法; 学习速度 |
课程来源: | 视频讲座网 |
数据采集: | 2020-11-22:yxd |
最后编审: | 2020-12-25:chenxin |
阅读次数: | 54 |