Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient State Representation Learning for Dynamic Robotic Scenarios   While the rapid progress of deep learning fuels end-to-end reinforcement
learning (RL), direct application, especially in high-dimensional space like
robotic scenarios still suffers from high sample efficiency. Therefore State
Representation Learning (SRL) is proposed to specifically learn to encode
task-relevant features from complex sensory data into low-dimensional states.
However, the pervasive implementation of SRL is usually conducted by a
decoupling strategy in which the observation-state mapping is learned
separately, which is prone to over-fit. To handle such problem, we present a
new algorithm called Policy Optimization via Abstract Representation which
integrates SRL into the original RL scale. Firstly, We engage RL loss to assist
in updating SRL model so that the states can evolve to meet the demand of
reinforcement learning and maintain a good physical interpretation. Secondly,
we introduce a dynamic parameter adjustment mechanism so that both models can
efficiently adapt to each other. Thirdly, we introduce a new prior called
domain resemblance to leverage expert demonstration to train the SRL model.
Finally, we provide a real-time access by state graph to monitor the course of
learning. Results show that our algorithm outperforms the PPO baselines and
decoupling strategies in terms of sample efficiency and final rewards. Thus our
model can efficiently deal with tasks in high dimensions and facilitate
training real-life robots directly from scratch.

26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph