We are excited to announce several significant updates to BEAR, the Physics-Principled Building Environment for Control and Reinforcement Learning.
New Features:
Improved User Interface: We have introduced the get_user_info() function to gather user inputs. This function offers an interactive and user-friendly experience to customize simulation parameters.
Customizable Reward Function: The reward function is now customizable, offering you the flexibility to design the reward to fit your specific research goals. This can be easily done through get_user_info() function as well.
Rewrite of the quickstart.py script: To improve readability and usage, we've rewritten the quickstart.py script to demonstrate how to initialize and use the environment.
Enhanced error detection and input validation: Our updated system is now more robust against incorrect or invalid user inputs.
We hope these updates make BEAR more useful and user-friendly for your research. We look forward to your feedback and encourage you to report any issues you may encounter.
Update Notice - BEAR v1.79
Dear BEAR users,
We are excited to announce several significant updates to BEAR, the Physics-Principled Building Environment for Control and Reinforcement Learning.
New Features:
get_user_info()
function to gather user inputs. This function offers an interactive and user-friendly experience to customize simulation parameters.get_user_info()
function as well.quickstart.py
script: To improve readability and usage, we've rewritten thequickstart.py
script to demonstrate how to initialize and use the environment.We hope these updates make BEAR more useful and user-friendly for your research. We look forward to your feedback and encourage you to report any issues you may encounter.
Best regards, The BEAR Team