metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_3_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-3
results:
- task:
type: sub-task
name: keep_all
task-id: 1
difficulty-id: 3
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 294.2457504272461 +/- 90.21479915391255
name: Cumulative Reward
verified: true
- type: collective_performance
value: 54.29261703491211 +/- 21.984864368274526
name: Collective Performance
verified: true
- type: individual_performance
value: 28.278907203674315 +/- 9.58957969827206
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 2.562152373790741 +/- 1.0673747521727917
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 235.63738784790038 +/- 85.44225993334209
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 3 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 1
Difficulty: 3
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment