metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_9_task_0_run_id_0_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-0-difficulty-9
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 9
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 108.30524711608886 +/- 44.26496456209219
name: Cumulative Reward
verified: true
- type: collective_performance
value: 48.16655330657959 +/- 18.658942149744412
name: Collective Performance
verified: true
- type: individual_performance
value: 23.520054149627686 +/- 8.724727286979716
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 50.061480331420896 +/- 27.6190461058019
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 3.3466444194316862 +/- 1.8331136243834456
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 9 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 0
Difficulty: 9
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment