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Found 2 papers, 2 papers with code
Learning Concise Models from Long Execution Traces
Abstract models of system-level behaviour have applications in design exploration, analysis, testing and verification.
Formal Languages and Automata Theory Software Engineering
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning
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 towards the reward requires achieving an unknown sequence of high-level objectives.
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