There are 0 repository under cross-entropy-method topic.
Implementation and visualization (some demos) of search and optimization algorithms.
Model-based reinforcement learning using CEM, MPC and PETS
Efficient Model-Based Deep Reinforcement Learning with Predictive Control: Developed a Model-Based RL algorithm using MPC, achieving convergence in 200 episodes (best case) and 1000 episodes on average, outperforming SAC/DQN (10,000+ episodes). Enhanced sample efficiency by 80-90% using learned dynamics and CEM for trajectory optimization.
CE-ABC is a code to simulate the epidemic outbreaks with mechanistic models through a cross-entropy approximate Bayesian framework.
Cross Entropy Method (CEM) implemented under Pytorch, supporting batch dimension and receding horizon style optimization.
Solving Tetris using Cross-Entropy Method
CEopt is a Matlab routine for non-convex optimization using the Cross-Entropy method and augmented Lagrangian formulation.
Simulation experiments for optimizing objective function with Differential Evolution, Evolution Strategies and Cross Entropy Method (2 versions)
Model-Based RL Multi-Tasking with ReLAx
Reinforcement Learning Notebooks
Train a Cross-Entropy Method in Policy-Based Methods with OpenAI Gtm's MountainCarContinous environment
Simple implementation and comparison of three reinforcement learning models.
CROSS-OPT is a Matlab package for optimizing truss structures with the Cross-Entropy method and augmented Lagrangian formulation.
FraCTune is a Matlab package for tuning fractional-order controllers with the Cross-Entropy method and augmented Lagrangian formulation.
SpringpotTune is a Matlab package designed for fitting variable-order springpot models using the Cross-Entropy method.
Two dimensional optimisation algorithm using the Cross Entropy Method. Data is iteratively fitted to a Beta Distribution in the algorithm.
Tools for using motion primitives like Dynamic Motion Primitives or Differentiable Linear Dynamic Systems in PyTorch.
Automated tuning of hyperparameters using Cross Entropy Method for optimization (CEM).
A Monte Carlo method for importance sampling and optimization.
Implementation of deep reinforcement learning
Implementation of base DL tasks
Cross-Entropy method example on OpenAI Gym's MountainCarContinuous environment. Code is from Udacity's "Deep Reinforcement Learning Nanodegree Program"
Workshop code for the talk on Introduction to Reinforcement Learning: https://fosterelli.co/file/talk/introduction-to-reinforcement-learning.pdf
Fifth assignment for Machine Learning course @USI19/20.
Open AI Cartpole environment gradient ascent
Example CEM implementation with ReLAx
CartPole-CrossEntropyMethod
A neural-network controller for a differential-drive agent to reach a goal.