Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Morphological Computation and Learning to Learn In Natural Intelligent
  Systems And AI   At present, artificial intelligence in the form of machine learning is making
impressive progress, especially the field of deep learning (DL) [1]. Deep
learning algorithms have been inspired from the beginning by nature,
specifically by the human brain, in spite of our incomplete knowledge about its
brain function. Learning from nature is a two-way process as discussed in
[2][3][4], computing is learning from neuroscience, while neuroscience is
quickly adopting information processing models. The question is, what can the
inspiration from computational nature at this stage of the development
contribute to deep learning and how much models and experiments in machine
learning can motivate, justify and lead research in neuroscience and cognitive
science and to practical applications of artificial intelligence.

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The categories of this paper are: hep-ph
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
6
The categories of this paper are: astro-ph