Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: From Machine Learning to Robotics: Challenges and Opportunities for
  Embodied Intelligence   Machine learning has long since become a keystone technology, accelerating
science and applications in a broad range of domains. Consequently, the notion
of applying learning methods to a particular problem set has become an
established and valuable modus operandi to advance a particular field. In this
article we argue that such an approach does not straightforwardly extended to
robotics -- or to embodied intelligence more generally: systems which engage in
a purposeful exchange of energy and information with a physical environment. In
particular, the purview of embodied intelligent agents extends significantly
beyond the typical considerations of main-stream machine learning approaches,
which typically (i) do not consider operation under conditions significantly
different from those encountered during training; (ii) do not consider the
often substantial, long-lasting and potentially safety-critical nature of
interactions during learning and deployment; (iii) do not require ready
adaptation to novel tasks while at the same time (iv) effectively and
efficiently curating and extending their models of the world through targeted
and deliberate actions. In reality, therefore, these limitations result in
learning-based systems which suffer from many of the same operational
shortcomings as more traditional, engineering-based approaches when deployed on
a robot outside a well defined, and often narrow operating envelope. Contrary
to viewing embodied intelligence as another application domain for machine
learning, here we argue that it is in fact a key driver for the advancement of
machine learning technology. In this article our goal is to highlight
challenges and opportunities that are specific to embodied intelligence and to
propose research directions which may significantly advance the
state-of-the-art in robot learning.

21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
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The categories of this paper are: atom-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol