-
Safe-Policy-Optimization
NeurIPS 2023: Safe Policy Optimization: A benchmark repository for safe reinforcement learning algorithms
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
We develop a modification to the Panda Gym by adding constraints to the environments like Unsafe regions and, constraints on the task. The aim is to develop an environment to test CMDPs (Constraint Markov Decision Process) / Safe-RL algorithms such as CPO, PPO - Lagrangian and algorithms developed by the team. Agents would not only have to come up with optimal policy for control and planning but also ensure they don't violate a constraint.
Support SafePO-Baselines to train the safe environments in our repo, which can be seen in the train_safe_rl_algorithms folder.
URL: https://github.com/tohsin/Safe-panda-gym.git