metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_1_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-1
results:
- task:
type: main-task
name: main_task
task-id: 0
difficulty-id: 1
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 93.91741180419922 +/- 37.05853273475244
name: Cumulative Reward
verified: true
- type: collective_performance
value: 34.50206546783447 +/- 11.805853483736035
name: Collective Performance
verified: true
- type: individual_performance
value: 18.018507194519042 +/- 6.813722115047946
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 49.37095775604248 +/- 24.763152240827306
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 0.2246590718626976 +/- 0.10528075262454495
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 1 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 0
Difficulty: 1
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment