Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The StreetLearn Environment and Dataset   Navigation is a rich and well-grounded problem domain that drives progress in
many different areas of research: perception, planning, memory, exploration,
and optimisation in particular. Historically these challenges have been
separately considered and solutions built that rely on stationary datasets -
for example, recorded trajectories through an environment. These datasets
cannot be used for decision-making and reinforcement learning, however, and in
general the perspective of navigation as an interactive learning task, where
the actions and behaviours of a learning agent are learned simultaneously with
the perception and planning, is relatively unsupported. Thus, existing
navigation benchmarks generally rely on static datasets (Geiger et al., 2013;
Kendall et al., 2015) or simulators (Beattie et al., 2016; Shah et al., 2018).
To support and validate research in end-to-end navigation, we present
StreetLearn: an interactive, first-person, partially-observed visual
environment that uses Google Street View for its photographic content and broad
coverage, and give performance baselines for a challenging goal-driven
navigation task. The environment code, baseline agent code, and the dataset are
available at http://streetlearn.cc

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The categories of this paper are: solv-int
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The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
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The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg
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The categories of this paper are: q-fin
3
The categories of this paper are: physics