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metadata
library_name: hivex
original_train_name: AerialWildfireSuppression_difficulty_9_task_0_run_id_1_train
tags:
  - hivex
  - hivex-aerial-wildfire-suppression
  - reinforcement-learning
  - multi-agent-reinforcement-learning
model-index:
  - name: hivex-AWS-PPO-baseline-task-0-difficulty-9
    results:
      - task:
          type: main-task
          name: main_task
          task-id: 0
          difficulty-id: 9
        dataset:
          name: hivex-aerial-wildfire-suppression
          type: hivex-aerial-wildfire-suppression
        metrics:
          - type: crash_count
            value: 0.24166667386889457 +/- 0.1750104476777611
            name: Crash Count
            verified: true
          - type: extinguishing_trees
            value: 17.141666746139528 +/- 39.513165920891936
            name: Extinguishing Trees
            verified: true
          - type: extinguishing_trees_reward
            value: 85.70833311080932 +/- 197.56582920337453
            name: Extinguishing Trees Reward
            verified: true
          - type: fire_out
            value: 0.12500000223517418 +/- 0.24106852927463382
            name: Fire Out
            verified: true
          - type: fire_too_close_to_city
            value: 0.9 +/- 0.2615741818902984
            name: Fire too Close to City
            verified: true
          - type: preparing_trees
            value: 721.7666670084 +/- 737.4681856167363
            name: Preparing Trees
            verified: true
          - type: preparing_trees_reward
            value: 721.7666670084 +/- 737.4681856167363
            name: Preparing Trees Reward
            verified: true
          - type: water_drop
            value: 66.28333377838135 +/- 30.644495531353783
            name: Water Drop
            verified: true
          - type: water_pickup
            value: 65.93333344459533 +/- 30.521844562150648
            name: Water Pickup
            verified: true
          - type: cumulative_reward
            value: 996.1558359742164 +/- 875.8416918638716
            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 9 using the Proximal Policy Optimization (PPO) algorithm.

Environment: Aerial Wildfire Suppression
Task: 0
Difficulty: 9
Algorithm: PPO
Episode Length: 3000
Training max_steps: 1800000
Testing max_steps: 180000

Train & Test Scripts
Download the Environment