Maze Navigator

 

artifact (share)

Train the robot to cross the road.

 Train the robot in the following scenario to cross the road.

scenario setting artifact

artifact (share)

Robot Walk RL

 Robot Walk RL Gemini 3 Pro

Robot Walk RL, Opus 4.5 (share)

Simulating BLUE LED

  Blue LED

Simulating Laser

 雷射(2d 模擬 energy pumping)

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雷射(3d 模擬) 使用3d量子場

share (He-Ne)

artifact

coherent emission in lattice

Verification of AI

  verify geo modeling

HW#12 Reinforcement Learning (RL) 2

 自行決定是否做作業，做的話任選一題即可

1. 市區交通模擬，如何控制燈號以增進運輸量 (RL)

    Birds' eye view and follow mode

 (credit: 與專題生共同創作)

sample, share

 2. Use RL to train Submarine to avoid unmanned torpedo from attaching and attacking

RL

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hi accomp share (artifact)

3. Use RL to optimize a Manufacturing Process overcoming a failure,  artifact (share) (inspired by Edward Chang)

  Job Shop

artifact (share)

4. Use RL to train inverted pendulum

artifact (share)

5. Train the robot in the following scenario to cross the road.

scenario setting artifact

artifact (share)

6. Use RL to train submarine maneuvers

Destroyer vs Submarine, share

RL artifact (share), h. accomplished, tactical

Job Shop RL

Visualization of Manufacturing Process,  simulation of pipelines (inspired by Edward Chang)

 

  Job Shop

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RL (Reinforcement Learning)

• Inverted Pendulum (RL)
•  drone training, terrain (share)
• maze navigator
• Train the robot to cross the road.
• Robot Walk RL
• 
  

• RL for ChungLi Traffic 400 tiers
• Job Shop RL

• RL for Submarine Tactical Operation
• RL for Submarine Maneuvers
• 
  

Protein Folding artifact  html

highly accomplished (share)

highly accomplish it artifact improved on student work

2 highly accomplish it artifact improved on student work

Inverted Pendulum (RL)

 

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Follow up #11 (RL)

 drone training (share)

RL for Submarine Tactical Operation

 

Destroyer vs Submarine, share

RL artifact (share), h. accomplished, tactical

RL for Submarine Maneuvers

 Use RL to train Submarine to avoid unmanned torpedo from attaching and attacking

RL

share (artifact)

hi accomp share (artifact)

RL for ChungLi Traffic 400 tiers

 市區交通模擬，如何控制燈號以增進運輸量 (RL)

    Birds' eye view and follow mode

 (credit: 與專題生共同創作)

sample, share

🚦 RL Traffic Control — Train, Save, Compare

Agents persist across sessions • Continue training anytime

🎮 Training (1747 episodes)

1x5x10x20x

1747

Episodes

5%

Exploration

1358079

Q-Table

-303.5

Avg R (10)

Learning Curve

🚦 RL Traffic Control — Train, Save, Compare

Agents persist across sessions • Continue training anytime

📊 Comparison Complete

Metric

❌ Untrained

✅ Trained (1688 eps)

Total Reward

-359.8

-158.8(+56%)

Throughput

17

21

Avg Wait

44.3

29.2

✓ Learning Verified! Trained agent outperformed random.