CORDIS Project
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This project aims to enhance reinforcement learning algorithms to improve their efficiency and scalability for real-world applications like autonomous vehicles and energy systems. By analyzing Markov decision processes, it seeks to develop tools that ensure better performance in dynamic environments.
Reinforcement learning (RL) is an intensely studied subfield of machine learning concerned with sequential decision-making problems where a learning agent interacts with an unknown reactive environment while attempting to maximize its rewards.
In recent years, RL methods have gained significant popularity due to being the key technique behind some spectacular breakthroughs of artificial intelligence (AI) research, which renewed interest in applying such techniques to challenging real-world probl…
UNIVERSIDAD POMPEU FABRA
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