--- library_name: hivex original_train_name: DroneBasedReforestation_difficulty_5_task_3_run_id_2_train tags: - hivex - hivex-drone-based-reforestation - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-DBR-PPO-baseline-task-3-difficulty-5 results: - task: type: sub-task name: drop_seed task-id: 3 difficulty-id: 5 dataset: name: hivex-drone-based-reforestation type: hivex-drone-based-reforestation metrics: - type: cumulative_distance_reward value: 1.317925215959549 +/- 0.28260177110908363 name: Cumulative Distance Reward verified: true - type: cumulative_distance_until_tree_drop value: 48.28620391845703 +/- 7.283860263327832 name: Cumulative Distance Until Tree Drop verified: true - type: cumulative_distance_to_existing_trees value: 64.57429847717285 +/- 5.444324231140867 name: Cumulative Distance to Existing Trees verified: true - type: cumulative_normalized_distance_until_tree_drop value: 0.13179252222180365 +/- 0.02826017752675318 name: Cumulative Normalized Distance Until Tree Drop verified: true - type: cumulative_tree_drop_reward value: 4.009531931877136 +/- 0.661158168654566 name: Cumulative Tree Drop Reward verified: true - type: out_of_energy_count value: 0.03808173710480332 +/- 0.021781055433560147 name: Out of Energy Count verified: true - type: recharge_energy_count value: 10.746735401153565 +/- 0.6862137746749559 name: Recharge Energy Count verified: true - type: tree_drop_count value: 0.9473729825019837 +/- 0.03268839810742225 name: Tree Drop Count verified: true - type: cumulative_reward value: 101.15483459472657 +/- 3.824644657818079 name: Cumulative Reward verified: true --- This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task 3 with difficulty 5 using the Proximal Policy Optimization (PPO) algorithm.

Environment: **Drone-Based Reforestation**
Task: 3
Difficulty: 5
Algorithm: PPO
Episode Length: 2000
Training max_steps: 1200000
Testing max_steps: 300000

Train & Test [Scripts](https://github.com/hivex-research/hivex)
Download the [Environment](https://github.com/hivex-research/hivex-environments)