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elevator-scheduling

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kumarpiyushraj / Smart-Elevator-Scheduling

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Intelligent elevator scheduling using QR-DQN with Dueling Networks and Prioritized Experience Replay. Achieves ~38% improvement over SCAN baseline. Published at IEEE AICAPS 2026. DOI: 10.1109/AICAPS68631.2026.11452978

python reinforcement-learning simulation pytorch deep-q-network dueling-network-architecture quantile-regression prioritized-experience-replay elevator-scheduling distributional-rl ieee-published
  • Updated Apr 26, 2026
  • Jupyter Notebook

kumarpiyushraj / Deep-MARL-Elevator-QRDQN-PyTorch

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Multi-agent elevator dispatch with QR-DQN and CTDE (Centralised Training, Decentralised Execution) in PyTorch. Three cooperative elevators trained with dueling networks, prioritised replay, and a centralised critic — beating ETA-Dispatch by 27% wait and 9.6% energy across 3,500 episodes on a non-uniform 10-floor traffic environment.

python reinforcement-learning deep-reinforcement-learning pytorch deep-q-network prioritized-replay quantile-regression dueling-dqn multi-agent-reinforcement-learning qr-dqn marl elevator-scheduling cooperative-ai decentralized-execution ctde
  • Updated Apr 26, 2026
  • Jupyter Notebook

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