Essays about: "deep Q-network"
Showing result 1 - 5 of 42 essays containing the words deep Q-network.
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1. Federated Machine Learning for Resource Allocation in Multi-domain Fog Ecosystems
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The proliferation of the Internet of Things (IoT) has increasingly demanded intimacy between cloud services and end-users. This has incentivised extending cloud resources to the edge in what is deemed fog computing. The latter is manifesting as an ecosystem of connected clouds, geo-dispersed and of diverse capacities. READ MORE
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2. Enhancing video game experience with playtime training and tailoring of virtual opponents : Using Deep Q-Network based Reinforcement Learning on a Multi-Agent Environment
University essay fromAbstract : When interacting with fictional environments, the users' sense of immersion can be broken when characters act in mechanical and predictable ways. The vast majority of AIs for such fictional characters, that control their actions, are statically scripted, and expert players can learn strategies that take advantage of this to easily win challenges that were intended to be hard. READ MORE
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3. An efficient deep reinforcement learning approach to the energy management for a parallel hybrid electric vehicle
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : In contemporary world, the global energy crisis and raise of greenhouse gas concentration in atmosphere necessitate the energy conservation and emission reduction. Hybrid electric vehicles (HEVs) can achieve great promise in reducing fuel consumption and greenhouse gas emissions by appropriate energy management strategies (EMSs). READ MORE
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4. 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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5. Control Method for an Automated Forest Machine Based on Deep Reinforcement Learning
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : An automated forest machine was designed in order to improve the working environment of today’s forest machine operators. In order to realize the autonomous control of the forest machine, model-based methods such as A* and dynamic window were used in previous projects. READ MORE
