Essays about: "dynamic policy analysis"
Showing result 16 - 20 of 92 essays containing the words dynamic policy analysis.
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16. Renewable Energy Sources and Energy Poverty
University essay from Lunds universitet/Ekonomisk-historiska institutionenAbstract : The availability of energy is an overarching measure connected to various aspects of poverty. Energy Poverty, as a concept, captures the deprivation of access to energy, clean and safe fuels and end-appliances. READ MORE
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17. Avoiding local minima with Genetic programming of Behavior Trees
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Behavior Trees (BTs) are a reactive policy representation that has gained popularity in recent years, especially in the robotics domain. Among the learning methods for BTs, Genetic Programming (GP) is an effective method for learning a good BT. One drawback of GP is that it is likely to get stuck in local minima. READ MORE
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18. Dynamic simulation of transforming the transport system - Based on Lotka-Volterra population modelling
University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesignAbstract : The transport sector plays a critical role in meeting the targets of achieving net-zero emissions. In comparison to traditional fuel vehicles (ICEVs), new energy vehicles, such as electric vehicles (EVs), have advantages of energy-saving and emission reduction. READ MORE
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19. Upscaling Electronics Repair to Support a Circular Economy in Sweden: A Focus on Cellphones Through the Lens of Policy Intervention
University essay from Lunds universitet/Internationella miljöinstitutetAbstract : E-waste is a growing waste problem around the world, and Sweden is no exception. However, the Swedish WEEE system is having issues combating the problem – particularly when it comes to cellphones. READ MORE
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20. Explainable Reinforcement Learning for Risk Mitigation in Human-Robot Collaboration Scenarios
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Reinforcement Learning (RL) algorithms are highly popular in the robotics field to solve complex problems, learn from dynamic environments and generate optimal outcomes. However, one of the main limitations of RL is the lack of model transparency. This includes the inability to provide explanations of why the output was generated. READ MORE