Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: POETREE: Interpretable Policy Learning with Adaptive Decision Trees   Building models of human decision-making from observed behaviour is critical
to better understand, diagnose and support real-world policies such as clinical
care. As established policy learning approaches remain focused on imitation
performance, they fall short of explaining the demonstrated decision-making
process. Policy Extraction through decision Trees (POETREE) is a novel
framework for interpretable policy learning, compatible with fully-offline and
partially-observable clinical decision environments -- and builds probabilistic
tree policies determining physician actions based on patients' observations and
medical history. Fully-differentiable tree architectures are grown
incrementally during optimization to adapt their complexity to the modelling
task, and learn a representation of patient history through recurrence,
resulting in decision tree policies that adapt over time with patient
information. This policy learning method outperforms the state-of-the-art on
real and synthetic medical datasets, both in terms of understanding,
quantifying and evaluating observed behaviour as well as in accurately
replicating it -- with potential to improve future decision support systems.

33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
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The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: math-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: q-alg