Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: TauRieL: Targeting Traveling Salesman Problem with a deep reinforcement
  learning inspired architecture   In this paper, we propose TauRieL and target Traveling Salesman Problem (TSP)
since it has broad applicability in theoretical and applied sciences. TauRieL
utilizes an actor-critic inspired architecture that adopts ordinary feedforward
nets to obtain a policy update vector $v$. Then, we use $v$ to improve the
state transition matrix from which we generate the policy. Also, the state
transition matrix allows the solver to initialize from precomputed solutions
such as nearest neighbors. In an online learning setting, TauRieL unifies the
training and the search where it can generate near-optimal results in seconds.
The input to the neural nets in the actor-critic architecture are raw 2-D
inputs, and the design idea behind this decision is to keep neural nets
relatively smaller than the architectures with wide embeddings with the
tradeoff of omitting any distributed representations of the embeddings.
Consequently, TauRieL generates TSP solutions two orders of magnitude faster
per TSP instance as compared to state-of-the-art offline techniques with a
performance impact of 6.1\% in the worst case.

31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph