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Deep Reinforcement Learning - based Rotary Inverted Pendulum

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dc.contributor.advisor Tamimi, Hashem
dc.contributor.author Hroub, Qusai
dc.date.accessioned 2023-09-07T06:45:29Z
dc.date.available 2023-09-07T06:45:29Z
dc.date.issued 2021-12-01
dc.identifier.uri scholar.ppu.edu/handle/123456789/8954
dc.description no of pages 58 , هندسة حاسوب 25/2021
dc.description.abstract Artificial Intelligence systems have become a very important term in many engineering fields. Intelligent robot systems are an example of Intelligence systems (IS). To develop an IS, we need Intelligent control methods specially when the dimension of state space gets very huge and it is impossible to cover all states in traditional programming techniques with feasible time. This project aims to develop an intelligent algorithm based on deep reinforcement learning that can learn from the environment to make the rotary inverted pendulum stable in an upward position. The system is designed to be realized on a Raspberry Pi microcontroller. TensorFlow was used for implementing the deep reinforcement learning algorithm. The simulation result showed that the system was able to learn to balance the pendulum in an upward position that starts from a random state in a proper range en_US
dc.language.iso en en_US
dc.publisher جامعة بوليتكنك فلسطين - هندسة حاسوب en_US
dc.subject Deep Reinforcement Learning en_US
dc.subject Rotary en_US
dc.subject Inverted Pendulum en_US
dc.title Deep Reinforcement Learning - based Rotary Inverted Pendulum en_US
dc.type Other en_US


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