Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Visual Reinforcement Learning with Imagined Goals   For an autonomous agent to fulfill a wide range of user-specified goals at
test time, it must be able to learn broadly applicable and general-purpose
skill repertoires. Furthermore, to provide the requisite level of generality,
these skills must handle raw sensory input such as images. In this paper, we
propose an algorithm that acquires such general-purpose skills by combining
unsupervised representation learning and reinforcement learning of
goal-conditioned policies. Since the particular goals that might be required at
test-time are not known in advance, the agent performs a self-supervised
"practice" phase where it imagines goals and attempts to achieve them. We learn
a visual representation with three distinct purposes: sampling goals for
self-supervised practice, providing a structured transformation of raw sensory
inputs, and computing a reward signal for goal reaching. We also propose a
retroactive goal relabeling scheme to further improve the sample-efficiency of
our method. Our off-policy algorithm is efficient enough to learn policies that
operate on raw image observations and goals for a real-world robotic system,
and substantially outperforms prior techniques.

11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math