58 citations · 239 across the 22 of their papers we have counts for
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cs.LG2020★ 13 cited
DRIFT: Deep Reinforcement Learning for Functional Software Testing
Luke Harries, Rebekah Storan Clarke, Timothy Chapman +10
Efficient software testing is essential for productive software development and reliable user experiences. As human testing is inefficient and expensive, automated software testing…
cs.LG2020★ 16 cited
Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir, Kamil Ciosek
Specifying a Reinforcement Learning (RL) task involves choosing a suitable planning horizon, which is typically modeled by a discount factor. It is known that applying RL algorithm…