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- ---
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- library_name: hivex
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- original_train_name: AerialWildfireSuppression_difficulty_6_task_4_run_id_0_train
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- tags:
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- - hivex
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- - hivex-aerial-wildfire-suppression
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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-AWS-PPO-baseline-task-4-difficulty-6
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- results:
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- - task:
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- type: sub-task
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- name: protect_village
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- task-id: 4
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- difficulty-id: 6
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- dataset:
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- name: hivex-aerial-wildfire-suppression
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- type: hivex-aerial-wildfire-suppression
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- metrics:
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- - type: crash_count
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- value: 0.995833334326744 +/- 0.01863389536983029
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- name: Crash Count
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- verified: true
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- - type: extinguishing_trees
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- value: 0.4878607466816902 +/- 1.5825325244644477
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- name: Extinguishing Trees
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- verified: true
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- - type: extinguishing_trees_reward
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- value: 2.4393037766218186 +/- 7.912662831428387
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- name: Extinguishing Trees Reward
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- verified: true
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- - type: fire_too_close_to_city
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- value: 0.008012820780277253 +/- 0.024684854855393578
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- name: Fire too Close to City
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- verified: true
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- - type: preparing_trees
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- value: 277.3211982727051 +/- 28.61713074868279
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- name: Preparing Trees
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- verified: true
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- - type: preparing_trees_reward
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- value: 277.3211982727051 +/- 28.61713074868279
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- name: Preparing Trees Reward
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- verified: true
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- - type: water_drop
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- value: 1.76927210688591 +/- 0.30789056520294616
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- name: Water Drop
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- verified: true
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- - type: water_pickup
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- value: 1.76927210688591 +/- 0.30789056520294616
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- name: Water Pickup
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- verified: true
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- - type: cumulative_reward
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- value: 177.74845504760742 +/- 32.464829950692376
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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 **Aerial Wildfire Suppression** environment, trained and tested on task <code>4</code> with difficulty <code>6</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>
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-
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- Environment: **Aerial Wildfire Suppression**<br>
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- Task: <code>4</code><br>
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- Difficulty: <code>6</code><br>
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- Algorithm: <code>PPO</code><br>
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- Episode Length: <code>3000</code><br>
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- Training <code>max_steps</code>: <code>1800000</code><br>
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- Testing <code>max_steps</code>: <code>180000</code><br><br>
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-
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- Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>
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- Download the [Environment](https://github.com/hivex-research/hivex-environments)
 
 
 
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+ ---
2
+ library_name: hivex
3
+ original_train_name: AerialWildfireSuppression_difficulty_6_task_4_run_id_0_train
4
+ tags:
5
+ - hivex
6
+ - hivex-aerial-wildfire-suppression
7
+ - reinforcement-learning
8
+ - multi-agent-reinforcement-learning
9
+ model-index:
10
+ - name: hivex-AWS-PPO-baseline-task-4-difficulty-6
11
+ results:
12
+ - task:
13
+ type: sub-task
14
+ name: protect_village
15
+ task-id: 4
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+ difficulty-id: 6
17
+ dataset:
18
+ name: hivex-aerial-wildfire-suppression
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+ type: hivex-aerial-wildfire-suppression
20
+ metrics:
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+ - type: crash_count
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+ value: 0.995833334326744 +/- 0.01863389536983029
23
+ name: Crash Count
24
+ verified: true
25
+ - type: extinguishing_trees
26
+ value: 0.4878607466816902 +/- 1.5825325244644477
27
+ name: Extinguishing Trees
28
+ verified: true
29
+ - type: extinguishing_trees_reward
30
+ value: 2.4393037766218186 +/- 7.912662831428387
31
+ name: Extinguishing Trees Reward
32
+ verified: true
33
+ - type: fire_too_close_to_city
34
+ value: 0.008012820780277253 +/- 0.024684854855393578
35
+ name: Fire too Close to City
36
+ verified: true
37
+ - type: preparing_trees
38
+ value: 277.3211982727051 +/- 28.61713074868279
39
+ name: Preparing Trees
40
+ verified: true
41
+ - type: preparing_trees_reward
42
+ value: 277.3211982727051 +/- 28.61713074868279
43
+ name: Preparing Trees Reward
44
+ verified: true
45
+ - type: water_drop
46
+ value: 1.76927210688591 +/- 0.30789056520294616
47
+ name: Water Drop
48
+ verified: true
49
+ - type: water_pickup
50
+ value: 1.76927210688591 +/- 0.30789056520294616
51
+ name: Water Pickup
52
+ verified: true
53
+ - type: cumulative_reward
54
+ value: 177.74845504760742 +/- 32.464829950692376
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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 **Aerial Wildfire Suppression** environment, trained and tested on task <code>4</code> with difficulty <code>6</code> using the Proximal Policy Optimization (PPO) algorithm.<br><br>
60
+
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+ Environment: **Aerial Wildfire Suppression**<br>
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+ Task: <code>4</code><br>
63
+ Difficulty: <code>6</code><br>
64
+ Algorithm: <code>PPO</code><br>
65
+ Episode Length: <code>3000</code><br>
66
+ Training <code>max_steps</code>: <code>1800000</code><br>
67
+ Testing <code>max_steps</code>: <code>180000</code><br><br>
68
+
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+ Train & Test [Scripts](https://github.com/hivex-research/hivex)<br>
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+ Download the [Environment](https://github.com/hivex-research/hivex-environments)
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+
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+ [hivex-paper]: https://arxiv.org/abs/2501.04180