metadata
library_name: hivex
original_train_name: WindFarmControl_pattern_2_task_0_run_id_2_train
tags:
- hivex
- hivex-wind-farm-control
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WFC-PPO-baseline-task-0-pattern-2
results:
- task:
type: main-task
name: main_task
task-id: 0
pattern-id: 2
dataset:
name: hivex-wind-farm-control
type: hivex-wind-farm-control
metrics:
- type: cumulative_reward
value: 4591.301657714844 +/- 45.36518564904124
name: Cumulative Reward
verified: true
- type: individual_performance
value: 4591.0513525390625 +/- 46.63217206689972
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 2 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wind Farm Control
Task: 0
Pattern: 2
Algorithm: PPO
Episode Length: 5000
Training max_steps: 8000000
Testing max_steps: 8000000
Train & Test Scripts
Download the Environment