--- library_name: hivex original_train_name: DroneBasedReforestation_difficulty_8_task_0_run_id_1_train tags: - hivex - hivex-drone-based-reforestation - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-DBR-PPO-baseline-task-0-difficulty-8 results: - task: type: main-task name: main_task task-id: 0 difficulty-id: 8 dataset: name: hivex-drone-based-reforestation type: hivex-drone-based-reforestation metrics: - type: cumulative_distance_reward value: 2.231035829782486 +/- 0.8328265468613688 name: Cumulative Distance Reward verified: true - type: cumulative_distance_until_tree_drop value: 66.65770332336426 +/- 16.760894397204105 name: Cumulative Distance Until Tree Drop verified: true - type: cumulative_distance_to_existing_trees value: 61.44380241394043 +/- 13.630261327963224 name: Cumulative Distance to Existing Trees verified: true - type: cumulative_normalized_distance_until_tree_drop value: 0.22310358494520188 +/- 0.08328265504237621 name: Cumulative Normalized Distance Until Tree Drop verified: true - type: cumulative_tree_drop_reward value: 5.744872629642487 +/- 1.9187415652465019 name: Cumulative Tree Drop Reward verified: true - type: out_of_energy_count value: 0.9406349241733551 +/- 0.06549559550080679 name: Out of Energy Count verified: true - type: recharge_energy_count value: 10.602158679962159 +/- 1.2842570609336479 name: Recharge Energy Count verified: true - type: tree_drop_count value: 1.0329841363430023 +/- 0.06435620343022462 name: Tree Drop Count verified: true - type: cumulative_reward value: 8.81026906967163 +/- 3.1991946865922416 name: Cumulative Reward verified: true --- This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task 0 with difficulty 8 using the Proximal Policy Optimization (PPO) algorithm.

Environment: **Drone-Based Reforestation**
Task: 0
Difficulty: 8
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)