Browsing Faculty of Science by Subject "Reinforcement learning"
Now showing items 1-5 of 5
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On deep learning in physics
(2021-04-01)Machine learning, and most notably deep neural networks, have seen unprecedented success in recent years due to their ability to learn complex nonlinear mappings by ingesting large amounts of data through the process of ... -
Perpetually playing physics
(2019-08-01)Here we discuss ideas of reinforcement learning and the importance of various aspects of it. We show how reinforcement learning methods based on genetic algorithms can be used to reproduce thermodynamic cycles without prior ... -
Preferential proximal policy optimization in reinforcement learning
(2023-12-01)The Proximal Policy Optimization (PPO), a policy gradient method, excels in reinforcement learning with its ”surrogate” objective function and stochastic gradient ascent. However, PPO does not fully consider the significance ... -
TCP congestion control using reinforcement learning
(2022-10-01)TCP, a transport layer protocol which ensures the reliable delivery of information on the network, is the basis of Internet connectivity, with 85% of the worlds Internet traffic being TCP based. TCP however, is slow to ... -
Using machine learning methods to aid scientists in laboratory environments
(2019-12-01)As machine learning gains popularity as a scientific instrument, we look to create methods to implement it as a laboratory tool for researchers. In the first of two projects, we discuss creating a real-time interference ...