metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_5_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-5
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 5
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 120.11513977050781 +/- 30.495234755057457
name: Cumulative Reward
verified: true
- type: collective_performance
value: 48.047623825073245 +/- 12.30012370845873
name: Collective Performance
verified: true
- type: individual_performance
value: 25.529859733581542 +/- 6.5168944140036675
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 63.44483680725098 +/- 18.86539940904601
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 0.6659428238868713 +/- 0.34641883158682535
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 5 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 0
Difficulty: 5
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment