Browsing by Subject "Deep Reinforcement Learning"
Now showing items 1-4 of 4
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Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2024)Reinforcement Learning (RL) enables an intelligent agent to optimise its performance in a task by continuously taking action from an observed state and receiving a feedback from the environment in form of rewards. RL ... -
Heterogeneous Multi-Agent Deep Reinforcement Learning for Traffic Lights Control
(2018)Reinforcement Learning (RL) has been extensively used in Urban Traffic Control (UTC) optimization due its capability to learn the dynamics of complex problems from interactions with the environment. Recent advances in ... -
Taking advantage of correlated information for energy-aware scheduling in the IoT: A deep reinforcement learning approach
(Trinity College Dublin. School of Engineering. Discipline of Electronic & Elect. Engineering, 2020)Millions of battery-powered sensors deployed for monitoring purposes in a multitude of scenarios, e.g., agriculture, smart cities, industry, etc., require energy-efficient solutions to prolong their lifetime. When these ... -
Using Deep Reinforcement Learning to Coordinate Multi-Modal Journey Planning with Limited Transportation Capacity
(2021)Multi-modal journey planning for large numbers of simultaneous travellers is a challenging prob- lem, particularly in the presence of limited transportation capacity. Fundamental trade-offs exist between balancing the ...