Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Isbell, Charles L."'
Autor:
Edwards, Ashley D., Isbell, Charles L.
Imitation by observation is an approach for learning from expert demonstrations that lack action information, such as videos. Recent approaches to this problem can be placed into two broad categories: training dynamics models that aim to predict the
Externí odkaz:
http://arxiv.org/abs/1905.07861
We address the problems of measuring geometric similarity between 3D scenes, represented through point clouds or range data frames, and associating them. Our approach leverages macro-scale 3D structural geometry - the relative configuration of arbitr
Externí odkaz:
http://arxiv.org/abs/1808.01343
In this paper, we describe a novel approach to imitation learning that infers latent policies directly from state observations. We introduce a method that characterizes the causal effects of latent actions on observations while simultaneously predict
Externí odkaz:
http://arxiv.org/abs/1805.07914
The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the
Externí odkaz:
http://arxiv.org/abs/1705.03321
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
Includes bibliographical references (p. [153]-160).
by Charles Lee Isbell, Junior.
Ph.D.
Includes bibliographical references (p. [153]-160).
by Charles Lee Isbell, Junior.
Ph.D.
Externí odkaz:
http://hdl.handle.net/1721.1/47513
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.
Includes bibliographical references (leaves 72-75).
by Charles L. Isbell.
M.S.
Includes bibliographical references (leaves 72-75).
by Charles L. Isbell.
M.S.
Externí odkaz:
http://hdl.handle.net/1721.1/12610
Autor:
Isbell, Charles L.
There has been recent interest in using temporal difference learning methods to attack problems of prediction and control. While these algorithms have been brought to bear on many problems, they remain poorly understood. It is the purpose of this the
Externí odkaz:
http://hdl.handle.net/1721.1/7050
Autor:
Cobo, Luis C. a, ⁎, Subramanian, Kaushik b, Isbell, Charles L., Jr. b, Lanterman, Aaron D. a, Thomaz, Andrea L. b
Publikováno v:
In Artificial Intelligence November 2014 216:103-128
In reinforcement learning, we often define goals by specifying rewards within desirable states. One problem with this approach is that we typically need to redefine the rewards each time the goal changes, which often requires some understanding of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8673f57e8402c505c9c492a234798b15
http://arxiv.org/abs/1705.09045
http://arxiv.org/abs/1705.09045
Akademický článek
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