--- library_name: hivex original_train_name: DroneBasedReforestation_difficulty_5_task_0_run_id_2_train tags: - hivex - hivex-drone-based-reforestation - reinforcement-learning - multi-agent-reinforcement-learning model-index: - name: hivex-DBR-PPO-baseline-task-0-difficulty-5 results: - task: type: main-task name: main_task task-id: 0 difficulty-id: 5 dataset: name: hivex-drone-based-reforestation type: hivex-drone-based-reforestation metrics: - type: cumulative_distance_reward value: 2.7580876886844634 +/- 0.7562888045399391 name: Cumulative Distance Reward verified: true - type: cumulative_distance_until_tree_drop value: 78.29452056884766 +/- 14.296043451183179 name: Cumulative Distance Until Tree Drop verified: true - type: cumulative_distance_to_existing_trees value: 50.473754501342775 +/- 11.98073606874106 name: Cumulative Distance to Existing Trees verified: true - type: cumulative_normalized_distance_until_tree_drop value: 0.2758087694644928 +/- 0.07562888371330763 name: Cumulative Normalized Distance Until Tree Drop verified: true - type: cumulative_tree_drop_reward value: 7.088011031150818 +/- 1.7168094182484812 name: Cumulative Tree Drop Reward verified: true - type: out_of_energy_count value: 0.9958095240592957 +/- 0.022119619288807686 name: Out of Energy Count verified: true - type: recharge_energy_count value: 9.258539686203003 +/- 0.587428694662249 name: Recharge Energy Count verified: true - type: tree_drop_count value: 0.9893650794029236 +/- 0.03160683668166852 name: Tree Drop Count verified: true - type: cumulative_reward value: 10.612933225631714 +/- 2.659049482325796 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 5 using the Proximal Policy Optimization (PPO) algorithm.

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