{
"client_config": {
"config_polling_seconds": 10,
"init_hyperparameters": {
"PPO": {
"discrete": true,
"seed": 0,
"traj_per_epoch": 1,
"clip_ratio": 0.1,
"gamma": 0.99,
"lam": 0.97,
"pi_lr": 3e-4,
"vf_lr": 3e-4,
"train_pi_iters": 40,
"train_v_iters": 40,
"target_kl": 0.01
},
"IPPO": {
"discrete": true,
"seed": 0,
"traj_per_epoch": 1,
"clip_ratio": 0.1,
"gamma": 0.99,
"lam": 0.97,
"pi_lr": 3e-4,
"vf_lr": 3e-4,
"train_pi_iters": 40,
"train_v_iters": 40,
"target_kl": 0.01
},
"MAPPO": {
"discrete": true,
"gamma": 0.99,
"lam": 0.97,
"clip_ratio": 0.2,
"pi_lr": 3e-4,
"vf_lr": 1e-3,
"train_pi_iters": 80,
"train_vf_iters": 80,
"target_kl": 0.01,
"traj_per_epoch": 8
},
"CUSTOM": {
"_comment": "Add custom algorithm hyperparams here formatted just like the other algorithms. i.e. \"MAPPO\": {...}",
"_comment2": "Make sure to add the algorithm name to the algorithm_name field",
"_comment3": "These key-values will be sent to the server for initialization"
}
},
"local_model_module": {
"directory": "model_module",
"model_name": "client_model",
"format": "pt"
},
"metrics": {
"meter_name": "relayrl-client",
"otlp_endpoint": {
"prefix": "http://",
"host": "127.0.0.1",
"port": "4317"
}
},
"trajectory_file_output": {
"directory": "experiment_data",
"_comment": "use `Csv` or `Arrow`",
"file_type": "Csv"
}
},
"transport_config": {
"nats_addresses": {
"inference_server_address": {
"host": "127.0.0.1",
"port": "50050"
},
"training_server_address": {
"host": "127.0.0.1",
"port": "50051"
}
},
"zmq_addresses": {
"inference_addresses": {
"inference_server_address": {
"host": "127.0.0.1",
"port": "7800"
},
"inference_scaling_server_address": {
"host": "127.0.0.1",
"port": "7801"
}
},
"training_addresses": {
"model_server_address": {
"host": "127.0.0.1",
"port": "50051"
},
"trajectory_server_address": {
"host": "127.0.0.1",
"port": "7776"
},
"agent_listener_address": {
"host": "127.0.0.1",
"port": "7777"
},
"training_scaling_server_address": {
"host": "127.0.0.1",
"port": "7778"
}
}
}
}
}