|
---
|
|
library_name: hivex
|
|
original_train_name: DroneBasedReforestation_difficulty_8_task_3_run_id_1_train
|
|
tags:
|
|
- hivex
|
|
- hivex-drone-based-reforestation
|
|
- reinforcement-learning
|
|
- multi-agent-reinforcement-learning
|
|
model-index:
|
|
- name: hivex-DBR-PPO-baseline-task-3-difficulty-8
|
|
results:
|
|
- task:
|
|
type: sub-task
|
|
name: drop_seed
|
|
task-id: 3
|
|
difficulty-id: 8
|
|
dataset:
|
|
name: hivex-drone-based-reforestation
|
|
type: hivex-drone-based-reforestation
|
|
metrics:
|
|
- type: cumulative_distance_reward
|
|
value: 1.3624776875972748 +/- 0.28554580887628567
|
|
name: Cumulative Distance Reward
|
|
verified: true
|
|
- type: cumulative_distance_until_tree_drop
|
|
value: 48.52491760253906 +/- 6.240952470711805
|
|
name: Cumulative Distance Until Tree Drop
|
|
verified: true
|
|
- type: cumulative_distance_to_existing_trees
|
|
value: 64.33281471252441 +/- 6.835068347254503
|
|
name: Cumulative Distance to Existing Trees
|
|
verified: true
|
|
- type: cumulative_normalized_distance_until_tree_drop
|
|
value: 0.13624776691198348 +/- 0.02855457901250283
|
|
name: Cumulative Normalized Distance Until Tree Drop
|
|
verified: true
|
|
- type: cumulative_tree_drop_reward
|
|
value: 4.091673822402954 +/- 0.9169991715461574
|
|
name: Cumulative Tree Drop Reward
|
|
verified: true
|
|
- type: out_of_energy_count
|
|
value: 0.03841008508577943 +/- 0.017628847741743853
|
|
name: Out of Energy Count
|
|
verified: true
|
|
- type: recharge_energy_count
|
|
value: 10.952794055938721 +/- 0.6585423813912649
|
|
name: Recharge Energy Count
|
|
verified: true
|
|
- type: tree_drop_count
|
|
value: 0.9443181335926056 +/- 0.027217821741009757
|
|
name: Tree Drop Count
|
|
verified: true
|
|
- type: cumulative_reward
|
|
value: 101.03555679321289 +/- 3.1604495163459303
|
|
name: Cumulative Reward
|
|
verified: true
|
|
---
|
|
|
|
This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task <code>3</code> with difficulty <code>8</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>8</code><br>Algorithm: <code>PPO</code><br>Episode Length: <code>2000</code><br>Training <code>max_steps</code>: <code>1200000</code><br>Testing <code>max_steps</code>: <code>300000</code><br><br>Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>Download the [Environment](https://github.com/hivex-research/hivex-environments) |