Hi, I have released version 0.19-1 of sfsim. This version introduces scaling of the graphical user interface.
Full notes
Full sfsim update
Read the full published notes in a cleaner layout. The original post stays linked below.
What changed
0 fixes0 additions2 changes0 removals
UI and audio
Performance
changedThis version introduces scaling of the graphical user interface. All the user interface elements are scaled up when switching to fullscreen or back taking into account the monitor resolution. This should make it easier to start implementing multi function displays (MFDs).
changedFurthermore I am working on launch trajectory optimization. It is not optimal yet as the rocket should first go up to leave the atmosphere more quickly. I am using proximal policy optimization (PPO) which is a reinforcement learning method which has become popular. Hopefully PPO will be able to also solve the more difficult problem of reentry. If you want to know more about this reinforcement learning method, I posted an article about PPO at ClojureCivitas .
sfsim changes
changedThis version introduces scaling of the graphical user interface. All the user interface elements are scaled up when switching to fullscreen or back taking into account the monitor resolution. This should make it easier to start implementing multi function displays (MFDs).
changedFurthermore I am working on launch trajectory optimization. It is not optimal yet as the rocket should first go up to leave the atmosphere more quickly. I am using proximal policy optimization (PPO) which is a reinforcement learning method which has become popular. Hopefully PPO will be able to also solve the more difficult problem of reentry. If you want to know more about this reinforcement learning method, I posted an article about PPO at ClojureCivitas .
This version introduces scaling of the graphical user interface. All the user interface elements are scaled up when switching to fullscreen or back taking into account the monitor resolution. This should make it easier to start implementing multi function displays (MFDs).
Furthermore I am working on launch trajectory optimization. It is not optimal yet as the rocket should first go up to leave the atmosphere more quickly. I am using proximal policy optimization (PPO) which is a reinforcement learning method which has become popular. Hopefully PPO will be able to also solve the more difficult problem of reentry. If you want to know more about this reinforcement learning method, I posted an article about PPO at ClojureCivitas.
