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Updated README

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Dominik Moritz Roth 2024-10-02 19:22:38 +02:00
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@ -102,15 +102,17 @@ The `NuconEnv` class in `nucon/rl.py` provides a Gym-compatible environment for
- Observation space: Includes all readable parameters from the Nucon system. - Observation space: Includes all readable parameters from the Nucon system.
- Action space: Encompasses all writable parameters in the Nucon system. - Action space: Encompasses all writable parameters in the Nucon system.
- Step function: Applies actions to the Nucon system and returns new observations. - Step function: Applies actions to the Nucon system and returns new observations.
- Objective function: Allows for custom objective functions to be defined for training. - Objective function: Allows for predefined or custom objective functions to be defined for training.
### Usage ### Usage
Here's a basic example of how to use the RL environment: Here's a basic example of how to use the RL environment:
```python ```python
from nucon.rl import NuconEnv from nucon.rl import NuconEnv, Parameterized_Objectives
env = NuconEnv(objectives=['max_power'], seconds_per_step=5) env = NuconEnv(objectives=['max_power'], seconds_per_step=5)
# env2 = gym.make('Nucon-max_power-v0')
# env3 = NuconEnv(objectives=[Parameterized_Objectives['target_temperature'](goal_temp=600)], seconds_per_step=5)
obs, info = env.reset() obs, info = env.reset()
for _ in range(1000): for _ in range(1000):
@ -122,6 +124,8 @@ for _ in range(1000):
env.close() env.close()
``` ```
Objectives takes either strings of the name of predefined objectives, or lambda functions which take an observation and return a scalar reward. Final rewards are summed across all objectives. `info['objectives']` contains all objectives and their values.
## Testing ## Testing
NuCon includes a test suite to verify its functionality and compatibility with the Nucleares game. NuCon includes a test suite to verify its functionality and compatibility with the Nucleares game.