metadata
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_5_task_0_run_id_2_train
tags:
- hivex
- hivex-aerial-wildfire-suppression
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-AWS-PPO-baseline-task-0-difficulty-5
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 5
dataset:
name: hivex-aerial-wildfire-suppression
type: hivex-aerial-wildfire-suppression
metrics:
- type: crash_count
value: 0.10833333656191826 +/- 0.13545462085140367
name: Crash Count
verified: true
- type: extinguishing_trees
value: 21.558333230018615 +/- 22.116535318538975
name: Extinguishing Trees
verified: true
- type: extinguishing_trees_reward
value: 107.79166641235352 +/- 110.58267924973548
name: Extinguishing Trees Reward
verified: true
- type: fire_out
value: 0.3250000037252903 +/- 0.352414398829495
name: Fire Out
verified: true
- type: fire_too_close_to_city
value: 0.975 +/- 0.11180339887498947
name: Fire too Close to City
verified: true
- type: preparing_trees
value: 906.383334851265 +/- 686.9466761748455
name: Preparing Trees
verified: true
- type: preparing_trees_reward
value: 906.383334851265 +/- 686.9466761748455
name: Preparing Trees Reward
verified: true
- type: water_drop
value: 42.29166712760925 +/- 14.596310384142566
name: Water Drop
verified: true
- type: water_pickup
value: 41.733333349227905 +/- 14.532822126312558
name: Water Pickup
verified: true
- type: cumulative_reward
value: 1040.6658332824707 +/- 651.2068293319696
name: Cumulative Reward
verified: true
This model serves as the baseline for the Aerial Wildfire Suppression environment, trained and tested on task 0 with difficulty 5 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Aerial Wildfire Suppression
Task: 0
Difficulty: 5
Algorithm: PPO
Episode Length: 3000
Training max_steps: 1800000
Testing max_steps: 180000
Train & Test Scripts
Download the Environment