metadata
library_name: hivex
original_train_name: WildfireResourceManagement_difficulty_8_task_1_run_id_1_train
tags:
- hivex
- hivex-wildfire-resource-management
- reinforcement-learning
- multi-agent-reinforcement-learning
model-index:
- name: hivex-WRM-PPO-baseline-task-1-difficulty-8
results:
- task:
type: sub-task
name: keep_all
task-id: 1
difficulty-id: 8
dataset:
name: hivex-wildfire-resource-management
type: hivex-wildfire-resource-management
metrics:
- type: cumulative_reward
value: 355.44918060302734 +/- 174.7116155809256
name: Cumulative Reward
verified: true
- type: collective_performance
value: 60.788882446289065 +/- 27.499079077539847
name: Collective Performance
verified: true
- type: individual_performance
value: 32.571975231170654 +/- 15.25373718413003
name: Individual Performance
verified: true
- type: reward_for_moving_resources_to_neighbours
value: 1.6818679869174957 +/- 1.4253886392289061
name: Reward for Moving Resources to Neighbours
verified: true
- type: reward_for_moving_resources_to_self
value: 280.6448547363281 +/- 131.94279504724986
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 8 using the Proximal Policy Optimization (PPO) algorithm.
Environment: Wildfire Resource Management
Task: 1
Difficulty: 8
Algorithm: PPO
Episode Length: 500
Training max_steps: 450000
Testing max_steps: 45000
Train & Test Scripts
Download the Environment