Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Controlling an Inverted Pendulum with Policy Gradient Methods-A Tutorial   This paper provides the details of implementing two important policy gradient
methods to solve the inverted pendulum problem. These are namely the Deep
Deterministic Policy Gradient (DDPG) and the Proximal Policy Optimization (PPO)
algorithm. The problem is solved by using an actor-critic model where an
actor-network is used to learn the policy function and a critic network is to
evaluate the actor-network by learning to estimate the Q function. Apart from
briefly explaining the mathematics behind these two algorithms, the details of
python implementation are provided which helps in demystifying the underlying
complexity of the algorithm. In the process, the readers will be introduced to
OpenAI/Gym, Tensorflow 2.x and Keras utilities used for implementing the above
concepts.

10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg