Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques

Smart home energy management is complicated because of varying user preferences, expenses, and consumption. These dynamics are difficult for traditional systems to handle, but new developments in reinforcement learning and optimization may be able to help. The paper introduces a novel Demand Respons...

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