Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning with Training Wheels: Speeding up Training with a Simple
  Controller for Deep Reinforcement Learning   Deep Reinforcement Learning (DRL) has been applied successfully to many
robotic applications. However, the large number of trials needed for training
is a key issue. Most of existing techniques developed to improve training
efficiency (e.g. imitation) target on general tasks rather than being tailored
for robot applications, which have their specific context to benefit from. We
propose a novel framework, Assisted Reinforcement Learning, where a classical
controller (e.g. a PID controller) is used as an alternative, switchable policy
to speed up training of DRL for local planning and navigation problems. The
core idea is that the simple control law allows the robot to rapidly learn
sensible primitives, like driving in a straight line, instead of random
exploration. As the actor network becomes more advanced, it can then take over
to perform more complex actions, like obstacle avoidance. Eventually, the
simple controller can be discarded entirely. We show that not only does this
technique train faster, it also is less sensitive to the structure of the DRL
network and consistently outperforms a standard Deep Deterministic Policy
Gradient network. We demonstrate the results in both simulation and real-world
experiments.

26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom