77 citations · 182 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Reinforcement Learning for Temporal Logic Control Synthesis with Probabilistic Satisfaction Guarantees
Mohammadhosein Hasanbeig, Yiannis Kantaros, Alessandro Abate +3
Reinforcement Learning (RL) has emerged as an efficient method of choice for solving complex sequential decision making problems in automatic control, computer science, economics,…
Modular Deep Reinforcement Learning with Temporal Logic Specifications
Lim Zun Yuan, Mohammadhosein Hasanbeig, Alessandro Abate +1
We propose an actor-critic, model-free, and online Reinforcement Learning (RL) framework for continuous-state continuous-action Markov Decision Processes (MDPs) when the reward is…
Certified Reinforcement Learning with Logic Guidance
Hosein Hasanbeig, Daniel Kroening, Alessandro Abate
Reinforcement Learning (RL) is a widely employed machine learning architecture that has been applied to a variety of control problems. However, applications in safety-critical doma…