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Mohammadhosein Hasanbeig

2 accepted papers

2021

DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning

AAAI 2021technical

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. Our method employs a novel algorith…

2021

Modular Deep Reinforcement Learning for Continuous Motion Planning With Temporal Logic

RA-L 2021

This letter investigates the motion planning of autonomous dynamical systems modeled by Markov decision processes (MDP) with unknown transition probabilities over continuous state and action spaces. Linear temporal logic (LTL) is used to specify high-level tasks over infinite horizon, which can be c

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