Browsing by Subject "Reinforcement Learning"
Now showing items 21-38 of 38
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(2021-11-10)When streaming media in a cellular network environment with less than ideal resources, simple algorithms do not perform well by not prioritizing specific clients well enough. Therefore, intelligent network sharing must ...
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(2021-10-14)Many physical systems have underlying safety or capacity considerations that require that the control policy employed ensures the satisfaction of a set of constraints. For instance, in a data network, in addition to ...
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(2020-12-03)As robots and other intelligent agents move from simple environments to more complex, unstructured settings, modern deep reinforcement learning (RL) systems require an exponentially increasing number of samples for learning. ...
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(2023-07-10)In the case of resource-limited robots, such as low-power drones or 4-wheel vehicles, there can be a lack of sufficient onboard computation capabilities or battery limitations for implementing precise navigation models. ...
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(2015-09-21)We address the problem of controlling continuum manipulators and evaluate Reinforcement Learning to produce a control policy for a robotic platform. Our approach discretizes the state and action spaces to reduce the training ...
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(2021-07-30)The current study focuses on developing an autonomous vertical flight aircraft ship landing system by directly automating the established Navy helicopter ship landing procedure. The central idea involves visually tracking ...
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(2011-08-08)Unmanned Aerial Vehicles (UAVs) are being used more frequently in surveillance scenarios for both civilian and military applications. One such application addresses a UAV patrolling a perimeter, where certain stations can ...
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(2020-04-23)Bandit learning has been widely applied to handle the exploration-exploitation dilemma in sequential decision problems. To solve the dilemma, a large number of bandit algorithms have been proposed. While many of these ...
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(2019-10-18)Decision making under uncertainty is an important problem in engineering that is traditionally approached differently in each of the Stochastic optimal control, Reinforcement learning and Motion planning disciplines. One ...
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(2015-08-21)Water is a major contributing factor for plant growth and development. Agricultural water management is a major concern for agriculturists, as fresh water resources are being depleted and research in the area of water ...
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(2019-11-06)Nowadays, in order to provide customers with the best surfing experience through the wireless network. Companies started building modern wireless base stations with a large amount of algorithm-based parameters that can ...
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(2013-04-30)Reinforcement Learning has received a lot of attention over the years for systems ranging from static game playing to dynamic system control. Using Reinforcement Learning for control of dynamical systems provides the benefit ...
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(2010-01-16)Shape Memory Alloy actuators can be used for morphing, or shape change, by controlling their temperature, which is effectively done by applying a voltage difference across their length. Control of these actuators ...
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In this project, we implement and deploy reinforcement learning (RL) algorithms for path planning, decision making, and navigation tasks in autonomous vehicles, and compare them to traditional control algorithms. Various ...
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(2022-07-26)Collaborative robotics allows for automating complex manufacturing tasks in dynamic environments that require robust uncertainty handling by human operators. This has led to the need for developing efficient human-robot ...
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(2023-07-27)This research dissertation explores novel algorithms in the field of robust reinforcement learning (RL) that address the challenges of controlling dynamical systems in real-world scenarios. Classical reinforcement learning ...
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(2023-05-24)As the Internet becomes increasingly integrated into people’s daily lives, dealing with data that is presented with subjective bias becomes a challenging issue. One such issue is "subjective bias", which is the use of ...
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(2023-05-24)As the Internet becomes increasingly integrated into people’s daily lives, dealing with data that is presented with subjective bias becomes a challenging issue. One such issue is "subjective bias", which is the use of ...