Before revision: This paper studies the  safe reinforcement learning (RL) problem without assumptions about prior knowledge of the system dynamics and the constraint function .
After revision: This paper studies the safe reinforcement learning (RL) problem without assumptions about prior knowledge of the system dynamics and environment constraints given a significantly small number of violation budgets .