metadata
library_name: hivex
original_train_name: WindFarmControl_pattern_6_task_0_run_id_1_train
tags:
- hivex
- hivex-wind-farm-control
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WFC-PPO-baseline-task-0-pattern-6
results:
- task:
type: main-task
name: main_task
task-id: 0
pattern-id: 6
dataset:
name: hivex-wind-farm-control
type: hivex-wind-farm-control
metrics:
- type: cumulative_reward
value: 4597.647395019531 +/- 42.54293382504652
name: Cumulative Reward
verified: true
- type: individual_performance
value: 4597.578510742187 +/- 43.53561804434955
name: Individual Performance
verified: true
This model serves as the baseline for the Wind Farm Control environment, trained and tested on task 0 with pattern 6 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wind Farm Control
Task: 0
Pattern: 6
Algorithm: PPO
Episode Length: 5000
Training max_steps: 8000000
Testing max_steps: 8000000
Train & Test Scripts
Download the Environment