metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_9_task_1_run_id_2_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-1-difficulty-9
results:
- task:
type: sub-task
name: keep_all
task-id: 1
difficulty-id: 9
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 256.54253845214845 +/- 82.7350530070222
name: Cumulative Reward
verified: true
- type: collective_performance
value: 43.02604579925537 +/- 13.287361543787155
name: Collective Performance
verified: true
- type: individual_performance
value: 23.407614994049073 +/- 7.450801825115115
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 1.6655276775360108 +/- 0.5314602326491544
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 197.1991439819336 +/- 65.86970427316282
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 9 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 1
Difficulty: 9
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment