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hivex-DBR-PPO-baseline-task-3-difficulty-5

Reinforcement Learning
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hivex
hivex-drone-based-reforestation
multi-agent-reinforcement-learning
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- ---
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- library_name: hivex
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- original_train_name: DroneBasedReforestation_difficulty_5_task_3_run_id_2_train
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- tags:
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- - hivex
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- - hivex-drone-based-reforestation
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- - reinforcement-learning
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- - multi-agent-reinforcement-learning
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- model-index:
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- - name: hivex-DBR-PPO-baseline-task-3-difficulty-5
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- results:
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- - task:
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- type: sub-task
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- name: drop_seed
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- task-id: 3
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- difficulty-id: 5
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- dataset:
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- name: hivex-drone-based-reforestation
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- type: hivex-drone-based-reforestation
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- metrics:
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- - type: cumulative_reward
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- value: 101.15483459472657 +/- 3.824644657818079
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- name: "Cumulative Reward"
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- verified: true
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- - type: cumulative_distance_reward
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- value: 1.317925215959549 +/- 0.28260177110908363
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- name: "Cumulative Distance Reward"
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- verified: true
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- - type: cumulative_distance_until_tree_drop
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- value: 48.28620391845703 +/- 7.283860263327832
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- name: "Cumulative Distance Until Tree Drop"
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- verified: true
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- - type: cumulative_distance_to_existing_trees
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- value: 64.57429847717285 +/- 5.444324231140867
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- name: "Cumulative Distance to Existing Trees"
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- verified: true
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- - type: cumulative_normalized_distance_until_tree_drop
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- value: 0.13179252222180365 +/- 0.02826017752675318
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- name: "Cumulative Normalized Distance Until Tree Drop"
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- verified: true
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- - type: cumulative_tree_drop_reward
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- value: 4.009531931877136 +/- 0.661158168654566
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- name: "Cumulative Tree Drop Reward"
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- verified: true
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- - type: out_of_energy_count
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- value: 0.03808173710480332 +/- 0.021781055433560147
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- name: "Out of Energy Count"
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- verified: true
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- - type: recharge_energy_count
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- value: 10.746735401153565 +/- 0.6862137746749559
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- name: "Recharge Energy Count"
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- verified: true
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- - type: tree_drop_count
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- value: 0.9473729825019837 +/- 0.03268839810742225
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- name: "Tree Drop Count"
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- verified: true
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- ---
 
 
 
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+ ---
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+ library_name: hivex
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+ original_train_name: DroneBasedReforestation_difficulty_5_task_3_run_id_2_train
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+ tags:
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+ - hivex
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+ - hivex-drone-based-reforestation
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+ - reinforcement-learning
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+ - multi-agent-reinforcement-learning
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+ model-index:
10
+ - name: hivex-DBR-PPO-baseline-task-3-difficulty-5
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+ results:
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+ - task:
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+ type: sub-task
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+ name: drop_seed
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+ task-id: 3
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+ difficulty-id: 5
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+ dataset:
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+ name: hivex-drone-based-reforestation
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+ type: hivex-drone-based-reforestation
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+ metrics:
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+ - type: cumulative_distance_reward
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+ value: 1.317925215959549 +/- 0.28260177110908363
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+ name: Cumulative Distance Reward
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+ verified: true
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+ - type: cumulative_distance_until_tree_drop
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+ value: 48.28620391845703 +/- 7.283860263327832
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+ name: Cumulative Distance Until Tree Drop
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+ verified: true
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+ - type: cumulative_distance_to_existing_trees
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+ value: 64.57429847717285 +/- 5.444324231140867
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+ name: Cumulative Distance to Existing Trees
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+ verified: true
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+ - type: cumulative_normalized_distance_until_tree_drop
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+ value: 0.13179252222180365 +/- 0.02826017752675318
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+ name: Cumulative Normalized Distance Until Tree Drop
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+ verified: true
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+ - type: cumulative_tree_drop_reward
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+ value: 4.009531931877136 +/- 0.661158168654566
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+ name: Cumulative Tree Drop Reward
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+ verified: true
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+ - type: out_of_energy_count
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+ value: 0.03808173710480332 +/- 0.021781055433560147
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+ name: Out of Energy Count
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+ verified: true
45
+ - type: recharge_energy_count
46
+ value: 10.746735401153565 +/- 0.6862137746749559
47
+ name: Recharge Energy Count
48
+ verified: true
49
+ - type: tree_drop_count
50
+ value: 0.9473729825019837 +/- 0.03268839810742225
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+ name: Tree Drop Count
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+ verified: true
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+ - type: cumulative_reward
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+ value: 101.15483459472657 +/- 3.824644657818079
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+ name: Cumulative Reward
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+ verified: true
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+ ---
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+
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+ This model serves as the baseline for the **Drone-Based Reforestation** environment, trained and tested on task <code>3</code> with difficulty <code>5</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>Environment: **Drone-Based Reforestation**<br>Task: <code>3</code><br>Difficulty: <code>5</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)