metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_3_task_2_run_id_1_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-2-difficulty-3
results:
- task:
type: sub-task
name: distribute_all
task-id: 2
difficulty-id: 3
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 847.854150390625 +/- 435.0499360739894
name: Cumulative Reward
verified: true
- type: collective_performance
value: 56.47811775207519 +/- 24.134183224321095
name: Collective Performance
verified: true
- type: individual_performance
value: 29.25127182006836 +/- 12.721708037101477
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 744.5827880859375 +/- 449.5107633042511
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 0.1304140117019415 +/- 0.04689085615979681
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 2 with difficulty 3 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 2
Difficulty: 3
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment