Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Compositional Neural Programs with Recursive Tree Search and
  Planning   We propose a novel reinforcement learning algorithm, AlphaNPI, that
incorporates the strengths of Neural Programmer-Interpreters (NPI) and
AlphaZero. NPI contributes structural biases in the form of modularity,
hierarchy and recursion, which are helpful to reduce sample complexity, improve
generalization and increase interpretability. AlphaZero contributes powerful
neural network guided search algorithms, which we augment with recursion.
AlphaNPI only assumes a hierarchical program specification with sparse rewards:
1 when the program execution satisfies the specification, and 0 otherwise.
Using this specification, AlphaNPI is able to train NPI models effectively with
RL for the first time, completely eliminating the need for strong supervision
in the form of execution traces. The experiments show that AlphaNPI can sort as
well as previous strongly supervised NPI variants. The AlphaNPI agent is also
trained on a Tower of Hanoi puzzle with two disks and is shown to generalize to
puzzles with an arbitrary number of disk

9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys