Essays about: "lärande agent"
Showing result 1 - 5 of 25 essays containing the words lärande agent.
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1. Stabilizing Side Effects of Experience Replay With Different Network Sizes for Deep Q-Network
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This report investigates the effects of two different types of batch selection used for traininga Deep Reinforcement Learning agent in games. More specifically, the impact of thedifferent methods were tested for different sizes of Deep Neural Networks while using theDeep Q-Network (DQN) algorithm. READ MORE
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2. Improving Behavior Trees that Use Reinforcement Learning with Control Barrier Functions : Modular, Learned, and Converging Control through Constraining a Learning Agent to Uphold Previously Achieved Sub Goals
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis investigates combining learning action nodes in behavior trees with control barrier functions based on the extended active constraint conditions of the nodes and whether the approach improves the performance, in terms of training time and policy quality, compared to a purely learning-based approach. Behavior trees combine several behaviors, called action nodes, into one behavior by switching between them based on the current state. READ MORE
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3. Reinforcement Learning for Pickup and Delivery Systems
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this project multi-agent reinforcement learning (RL) for a warehouse environmentwith robots delivering packages has been studied. This was done by first implementing the RLalgorithm Q-learning and investigating how the parameters of Q-learning affect the performanceof the algorithm. READ MORE
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4. Explainable Reinforcement Learning for Gameplay
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : State-of-the-art Machine Learning (ML) algorithms show impressive results for a myriad of applications. However, they operate as a sort of a black box: the decisions taken are not human-understandable. READ MORE
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5. Link Adaptation in 5G Networks : Reinforcement Learning Framework based Approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Link Adaptation is a core feature introduced in gNodeB (gNB) for Adaptive Modulation and Coding (AMC) scheme in new generation cellular networks. The main purpose of this is to correct the estimated Signal-to-Interference-plus-Noise ratio (SINR) at gNB and select the appropriate Modulation and Coding Scheme (MCS) so the User Equipment (UE) can decode the data successfully. READ MORE
