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q-learning-algorithm

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albinjm / DeepTrafficQ

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DeepTrafficQ is a reinforcement learning-based traffic signal control system that uses Deep Q-Networks (DQN) to minimize vehicle waiting times at a 4-way intersection. By leveraging Q-learning with experience replay and a convolutional neural network (CNN), the agent dynamically adjusts traffic light phases to optimize traffic flow.

reinforcement-learning q-learning cnn sumo convolutional-neural-networks deep-q-network cnn-keras smart-cities smart-mobility traffic-optimization experience-replay adaptive-traffic-light-control traffic-signal-control intelligent-transportation q-learning-algorithm iot-traffic-surveillance dqn-agent intelligent-transportation-system
  • Updated Jun 29, 2025
  • C

spear97 / UE5-Q-Learning

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This is a Remake of the Senior Design Capstone that was created for the Spring Semester of 2022 at Texas Wesleyan University. I scaled down the Scope of the application, and the overall simulation focused on getting an AI Agent to Navigate a Maze to reach the location of a Goal in a Maze using Reinforcement Learning via the Q-Learning Algorithm.

machine-learning visual-studio cpp computer-graphics game-development q-learning artificial-intelligence unreal-engine object-oriented-programming capstone-project simulation-game unreal-blueprints q-learning-algorithm unreal-engine-5 simulation-programming
  • Updated Mar 16, 2024
  • C

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