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GitHub10y
mahaitongdae/Approximate-Dynamic-Programming: ADP demo code for Reinforcement Learning and Control, Tsinghua Univ. Lecture Notes. - GitHub
Approximate-Dynamic-Programming │ main.py - Main script │ plot.py - To plot comparison between ADP and MPC │ train.py - To execute PEV and PIM │ dynamics.py - Vehicle model │ network.py - Network ...
IEEE1y
Reinforcement Learning for Partially Observable Dynamic Processes: Adaptive Dynamic Programming Using Measured Output Data
Abstract: Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical ...
ETH Zurich4y
Dynamic Programming and Optimal Control - ETH Zürich
Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. ... and reinforcement learning etc. for both ...
GitHub7mon
GitHub - Jugraunaqsingh/Protein-Folding-Prediction-Model: The model simulates protein folding by combining Dynamic Programming (DP) and Reinforcement Learning (RL) to predict ...
The model simulates protein folding by combining Dynamic Programming (DP) and Reinforcement Learning (RL) to predict realistic, biologically plausible structures. It utilizes physics-based properties ...
IEEE15y
Reinforcement Learning for Partially Observable Dynamic Processes: Adaptive Dynamic Programming Using Measured Output Data | IEEE Journals & Magazine | IEEE Xplore
Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP ...