Add reinforcement learning
- Update the version to 0.3.0-SNAPSHOT
- Implement parameters for reinforcement learning (see README.md for detailed parameter information)
- Add more loss function parameters
- Add a convenient way to use multi parameter entries (see MultiParamValueSymbol)
- Add a RewardFunctionSymbol
- Add CoCo:
- From now on there are parameters exclusively for reinforcement learning and supervised learning. A check ensures that a parameter is used in the correct learning method context.
- If target network is used, a training interval is required
- Check that a reinforcement configuration always has information about the environment
- Given the ROS environment, a check ensures that a reward function is given