metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_3_task_0_run_id_1_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-0-difficulty-3
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 3
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 126.3875114440918 +/- 56.44168555104561
name: Cumulative Reward
verified: true
- type: collective_performance
value: 58.50737037658691 +/- 24.677273237197756
name: Collective Performance
verified: true
- type: individual_performance
value: 28.715758323669434 +/- 11.726221119633433
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 57.897673797607425 +/- 36.70665957655046
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 3.56278680562973 +/- 1.5159918271507633
name: Reward for Moving Resources to Self
verified: true
This model serves as the baseline for the Wildfire Resource Management environment, trained and tested on task 0 with difficulty 3 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 0
Difficulty: 3
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment