Essays about: "DDPG"
Showing result 1 - 5 of 13 essays containing the word DDPG.
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1. Deep reinforcement learning for automated building climate control
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : The building sector is the single largest contributor to greenhouse gas emissions, making it a natural focal point for reducing energy consumption. More efficient use of energy is also becoming increasingly important for property managers as global energy prices are skyrocketing. READ MORE
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2. Deep Reinforcement Learning Approach to Portfolio Optimization
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : This paper evaluates whether a deep reinforcement learning (DRL) approach can be implemented, on the Swedish stock market, to optimize a portfolio. The objective is to create and train two DRL algorithms that can construct portfolios that will be benchmarked against the market portfolio, tracking OMXS30, and the two conventional methods, the naive portfolio, and minimum variance portfolio. READ MORE
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3. 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
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4. Spiking Reinforcement Learning for Robust Robot Control Under Varying Operating Conditions
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over the last few years, deep reinforcement learning (RL) has gained increasing popularity for its successful application to a variety of complex control and decision-making tasks. As the demand for deep RL algorithms deployed in challenging real-world environments grows, their robustness towards uncertainty, disturbances and perturbations of the environment becomes more and more important. READ MORE
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5. Deep Reinforcement Learning for Dynamic Grasping
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Dynamic grasping is the action of, using only contact force, manipulating the position of a moving object in space. Doing so with a robot is a quite complex task in itself, but is one with wide-ranging applications. READ MORE
