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Notes on deep reinforcement learning
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Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections
The paper introduces a new deep reinforcement learning architecture called Master-Agent Proto-plan System (MAPS) for coordinating autonomous vehicles at unsignalized intersections. The MAPS system uses a centralized…
Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections
Researchers proposed a new system called Master-Agent Proto-plan System (MAPS) for coordinating autonomous vehicles at unsignalized intersections using deep reinforcement learning. MAPS outperformed state-of-the-art…
Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms
The paper proposes a multi-objective optimization control system for battery management in dairy farms using differential evolution and multi-agent deep reinforcement learning. The system aims to improve profits from…
State Representation Matters in Deep Reinforcement Learning: Application to Energy Trading
Researchers study the impact of state representation on a reinforcement learning agent in energy trading decisions, focusing on a pumped-storage arbitrage environment. They find that combining absolute price…
Dynamic multi-agent deep reinforcement learning-based pricing and incentivization approach in multimodal transportation networks
A research paper proposes a multi-agent deep reinforcement learning framework to address challenges in multimodal transportation systems, particularly regarding shared mobility services (SMSs) demand concentration and…
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