Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimizing the Long-Term Behaviour of Deep Reinforcement Learning for
  Pushing and Grasping   We investigate the "Visual Pushing for Grasping" (VPG) system by Zeng et al.
and the "Hourglass" system by Ewerton et al., an evolution of the former. The
focus of our work is the investigation of the capabilities of both systems to
learn long-term rewards and policies. Zeng et al. original task only needs a
limited amount of foresight. Ewerton et al. attain their best performance using
an agent which only takes the most immediate action under consideration. We are
interested in the ability of their models and training algorithms to accurately
predict long-term Q-Values. To evaluate this ability, we design a new bin
sorting task and reward function. Our task requires agents to accurately
estimate future rewards and therefore use high discount factors in their
Q-Value calculation. We investigate the behaviour of an adaptation of the VPG
training algorithm on our task. We show that this adaptation can not accurately
predict the required long-term action sequences. In addition to the limitations
identified by Ewerton et al., it suffers from the known Deep Q-Learning problem
of overestimated Q-Values. In an effort to solve our task, we turn to the
Hourglass models and combine them with the Double Q-Learning approach. We show
that this approach enables the models to accurately predict long-term action
sequences when trained with large discount factors. Our results show that the
Double Q-Learning technique is essential for training with very high discount
factors, as the models Q-Value predictions diverge otherwise. We also
experiment with different approaches for discount factor scheduling, loss
calculation and exploration procedures. Our results show that the latter
factors do not visibly influence the model's performance for our task.

15
The categories of this paper are: nucl-ex
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
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The categories of this paper are: eess
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
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The categories of this paper are: stat
12
The categories of this paper are: nucl-th
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The categories of this paper are: funct-an
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The categories of this paper are: chem-ph