2 papers
cs.FL2020
Learning Concise Models from Long Execution Traces
Natasha Yogananda Jeppu, Tom Melham, Daniel Kroening +1
Abstract models of system-level behaviour have applications in design exploration, analysis, testing and verification. We describe a new algorithm for automatically extracting usef…
cs.LG2019
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning
Mohammadhosein Hasanbeig, Natasha Yogananda Jeppu, Alessandro Abate +2
This paper proposes DeepSynth, a method for effective training of deep Reinforcement Learning (RL) agents when the reward is sparse and non-Markovian, but at the same time progress…