Essays about: "Qlearning"
Showing result 1 - 5 of 7 essays containing the word Qlearning.
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1. Implementing an OpenAI Gym for Machine Learning of Microgrid Electricity Trading
University essay from Mittuniversitetet/Institutionen för informationssystem och –teknologiAbstract : Samhället går idag bort från centraliserad energi mot decentraliserade system. Istället för att köpa från stora företag som skapar el från fossila bränslen har många förnybara alternativ kommit. Eftersom konsumenter kan generera solenergi med solpaneler kan de också bli producenter. READ MORE
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2. Deep Reinforcement Learning for the Popular Game tag
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Reinforcement learning can be compared to howhumans learn – by interaction, which is the fundamental conceptof this project. This paper aims to compare three differentlearning methods by creating two adversarial reinforcementlearning models and simulate them in the game tag. READ MORE
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3. Scaling up Maximum Entropy Deep Inverse Reinforcement Learning with Transfer Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this thesis an issue with common inverse reinforcement learning algorithms is identified, which causes them to be computationally heavy. A solution is proposed which attempts to address this issue and which can be built upon in the future. READ MORE
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4. Stuck state avoidance through PID estimation training of Q-learning agent
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Reinforcement learning is conceptually based on an agent learning through interaction with its environment. This trial-and-error learning method makes the process prone to situations in which the agent is stuck in a dead-end, from which it cannot keep learning. READ MORE
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5. Distributed Optimisation in Multi-Agent Systems Through Deep Reinforcement Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The increased availability of computing power have made reinforcement learning a popular field of science in the most recent years. Recently, reinforcement learning has been used in applications like decreasing energy consumption in data centers, diagnosing patients in medical care and in text-tospeech software. READ MORE