metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_5_task_2_run_id_2_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-2-difficulty-5
results:
- task:
type: sub-task
name: distribute_all
task-id: 2
difficulty-id: 5
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 784.7529388427735 +/- 237.5803281220698
name: Cumulative Reward
verified: true
- type: collective_performance
value: 46.654307174682614 +/- 12.41762735898119
name: Collective Performance
verified: true
- type: individual_performance
value: 25.153486728668213 +/- 6.66514805176298
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 685.7552093505859 +/- 200.96518835832964
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 0.3521461673080921 +/- 0.28661129618806847
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 2 with difficulty 5 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 2
Difficulty: 5
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment