Add to ORKGThe aim of this thesis is to use deep neural networks for task in reinforcement learning. I use my modification of 2D game Tuxánci for the purposes of the test environment. This modification provides the possibility of using the game as an environment for machine learning. Subsequently, Iam solving the task of learning the agent by using reinforcement learning with the Double DQN algorithm
Reinforcement learning has achieved tremendous success in recent years, notably in complex games suc...
In this project, we aim to reproduce previous resultsachieved with Deep Reinforcement Learning. We p...
The popular Q-learning algorithm is known to overestimate action values under certain conditions. It...
Cílem této práce je použití hlubokých neuronových sítí na problém v posilovaném učení. Používám moji...
Ever since the remarkable achievement of AlphaGo by Google in 2017, it has led to the growing intere...
The aim of this bachelor thesis is to teach a neural network solving classic control theory problems...
We present an implementation of a specific type of deep reinforcement learning algorithm known as de...
A previous study used the Antarjami gaming framework to determine the OCEAN personality traits. In t...
Reinforcement learning can be compared to howhumans learn – by interaction, which is the fundamental...
This thesis is focused on analysing deep learning algorithms and their ability to complete given tas...
In recent years, Machine Learning research has made notable progress using Deep Learning methods. De...
This report investigates the implementation of a Deep Reinforcement Learning (DRL) algorithm for com...
Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demon...
The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:131...
This thesis focuses on deep neural networks and reinforcement learning (a.k.a deep reinforcement lea...
Reinforcement learning has achieved tremendous success in recent years, notably in complex games suc...
In this project, we aim to reproduce previous resultsachieved with Deep Reinforcement Learning. We p...
The popular Q-learning algorithm is known to overestimate action values under certain conditions. It...
Cílem této práce je použití hlubokých neuronových sítí na problém v posilovaném učení. Používám moji...
Ever since the remarkable achievement of AlphaGo by Google in 2017, it has led to the growing intere...
The aim of this bachelor thesis is to teach a neural network solving classic control theory problems...
We present an implementation of a specific type of deep reinforcement learning algorithm known as de...
A previous study used the Antarjami gaming framework to determine the OCEAN personality traits. In t...
Reinforcement learning can be compared to howhumans learn – by interaction, which is the fundamental...
This thesis is focused on analysing deep learning algorithms and their ability to complete given tas...
In recent years, Machine Learning research has made notable progress using Deep Learning methods. De...
This report investigates the implementation of a Deep Reinforcement Learning (DRL) algorithm for com...
Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demon...
The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:131...
This thesis focuses on deep neural networks and reinforcement learning (a.k.a deep reinforcement lea...
Reinforcement learning has achieved tremendous success in recent years, notably in complex games suc...
In this project, we aim to reproduce previous resultsachieved with Deep Reinforcement Learning. We p...
The popular Q-learning algorithm is known to overestimate action values under certain conditions. It...