chore: draft new configs

src/brittle_star_project/configs/config_experiment.py

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+from dataclasses import dataclass
+
+
+@dataclass
+class ExperimentConfig:
+    exp_name: str = "brittle_star_ppo"
+    seed: int = 1
+    torch_deterministic: bool = True
+    cuda: bool = True

src/brittle_star_project/configs/config_networks.py

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+from dataclasses import dataclass, field
+from typing import List, Optional
+
+
+@dataclass
+class LayerConfig:
+    hidden_dims: List[int] = field(default_factory=lambda: [64, 64])
+    activation: str = "relu"
+
+
+@dataclass
+class MLPConfig:
+    actor: LayerConfig = field(default_factory=LayerConfig)
+    critic: LayerConfig = field(default_factory=LayerConfig)
+    sensor: LayerConfig = field(default_factory=LayerConfig)
+    feature_extractor: LayerConfig = field(default_factory=LayerConfig)
+
+
+@dataclass
+class NetworksConfig:
+    mlp: MLPConfig = field(default_factory=MLPConfig)
+    # Future placeholder for message_passing
+    # message_passing: Optional[MessagePassingConfig] = None

src/brittle_star_project/configs/config_ppo.py

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+from dataclasses import dataclass
+from typing import Optional
+
+
+@dataclass
+class PPOConfig:
+    learning_rate: float = 2.5e-4
+    total_timesteps: int = 10000000
+    num_envs: int = 100
+    num_steps: int = 128
+    anneal_lr: bool = True
+    gamma: float = 0.99
+    gae_lambda: float = 0.95
+    num_minibatches: int = 4
+    update_epochs: int = 4
+    norm_adv: bool = True
+    clip_coef: float = 0.1
+    clip_vloss: bool = True
+    ent_coef: float = 0.01
+    vf_coef: float = 0.5
+    max_grad_norm: float = 0.5
+    target_kl: Optional[float] = None

src/brittle_star_project/configs/main_config.py

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+from dataclasses import dataclass, field
+
+from experiment_logger.config_logger import LoggingConfig
+from brittle_star_project.configs.config_experiment import ExperimentConfig
+from brittle_star_project.configs.config_ppo import PPOConfig
+from brittle_star_project.configs.config_networks import NetworksConfig
+from brittle_star_project.environment.env_config import MorphologyConfig, ArenaConfig, EnvConfig
+
+
+@dataclass
+class BrittleStarConfig:
+    experiment: ExperimentConfig = field(default_factory=ExperimentConfig)
+    logging: LoggingConfig = field(default_factory=LoggingConfig)
+    ppo: PPOConfig = field(default_factory=PPOConfig)
+    networks: NetworksConfig = field(default_factory=NetworksConfig)
+    morphology: MorphologyConfig = field(default_factory=MorphologyConfig)
+    arena: ArenaConfig = field(default_factory=ArenaConfig)
+    environment: EnvConfig = field(default_factory=EnvConfig)

src/brittle_star_project/configs/register_configs.py

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+from hydra.core.config_store import ConfigStore
+
+from experiment_logger.config_logger import LoggingConfig
+from brittle_star_project.configs.config_experiment import ExperimentConfig
+from brittle_star_project.configs.config_ppo import PPOConfig
+from brittle_star_project.configs.config_networks import NetworksConfig, MLPConfig, LayerConfig
+from brittle_star_project.environment.env_config import MorphologyConfig, ArenaConfig, EnvConfig
+from brittle_star_project.configs.main_config import BrittleStarConfig
+
+
+def register_configs():
+    """Register dataclasses with Hydra's ConfigStore."""
+    cs = ConfigStore.instance()
+
+    # Store the main config schema
+    cs.store(name="brittle_star_config", node=BrittleStarConfig)
+
+    # Store individual structured configs for validation
+    cs.store(group="experiment", name="base_experiment", node=ExperimentConfig)
+    cs.store(group="logging", name="base_logging", node=LoggingConfig)
+    cs.store(group="ppo", name="base_ppo", node=PPOConfig)
+    cs.store(group="networks", name="base_networks", node=NetworksConfig)
+
+    # Environment configs (reusing existing environment config objects)
+    cs.store(group="morphology", name="base_morphology", node=MorphologyConfig)
+    cs.store(group="arena", name="base_arena", node=ArenaConfig)
+    cs.store(group="environment", name="base_environment", node=EnvConfig)

src/experiment_logger/config_logger.py

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+from dataclasses import dataclass
+from typing import Optional
+
+
+@dataclass
+class LoggingConfig:
+    track: bool = False
+    wandb_project_name: str = "PPO-Modularity"
+    wandb_entity: Optional[str] = "SEL3-2026-Groep-4"
+    capture_video: bool = False
+    save_model: bool = True
+    checkpoint_frequency: int = 100
+    upload_model: bool = False
+    hf_entity: str = ""