Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Shankar, Tanmay"'
Autor:
Shankar, Tanmay, Gupta, Abhinav
In this paper, we address the discovery of robotic options from demonstrations in an unsupervised manner. Specifically, we present a framework to jointly learn low-level control policies and higher-level policies of how to use them from demonstration
Externí odkaz:
http://arxiv.org/abs/2006.16232
We explore the problem of learning to decompose spatial tasks into segments, as exemplified by the problem of a painting robot covering a large object. Inspired by the ability of classical decision tree algorithms to construct structured partitions o
Externí odkaz:
http://arxiv.org/abs/1806.07822
Autor:
Salman, Hadi, Singhal, Puneet, Shankar, Tanmay, Yin, Peng, Salman, Ali, Paivine, William, Sartoretti, Guillaume, Travers, Matthew, Choset, Howie
Recent literature in the robotics community has focused on learning robot behaviors that abstract out lower-level details of robot control. To fully leverage the efficacy of such behaviors, it is necessary to select and sequence them to achieve a giv
Externí odkaz:
http://arxiv.org/abs/1803.01446
Deep Reinforcement Learning has enabled the learning of policies for complex tasks in partially observable environments, without explicitly learning the underlying model of the tasks. While such model-free methods achieve considerable performance, th
Externí odkaz:
http://arxiv.org/abs/1701.02392
The book includes research papers on current developments in the field of soft computing and signal processing, selected from papers presented at the International Conference on Soft Computing and Signal Processing (ICSCSP 2018). It features papers o