metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_1_task_1_run_id_0_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-1-difficulty-1
results:
- task:
type: sub-task
name: keep_all
task-id: 1
difficulty-id: 1
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 195.4663185119629 +/- 77.65158484674649
name: Cumulative Reward
verified: true
- type: collective_performance
value: 34.28780403137207 +/- 10.980421619205345
name: Collective Performance
verified: true
- type: individual_performance
value: 16.798346424102782 +/- 5.2696319909880085
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 1.2929230749607086 +/- 0.5330753884066604
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 143.07430686950684 +/- 44.849034918704156
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 1 with difficulty 1 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 1
Difficulty: 1
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment