KohlerHECTOR

aeirl-pytorch

A simple implementation of Auto-Encoding Inverse Reinforcement Learning with PyTorch

Bayesian-network-learning

Comparing learning algorithms based on constraints (in progress).

CrossEntropyMethod-VS-PolicyGradient

Simple library based on https://github.com/osigaud/Basic-Policy-Gradient-Labs made for the Master's project: Comparison of Evolutionnary Methods and Reinforcement Learning methods on classical control benchmarks. Supervised by Prof Olivier Sigaud with Damien Legros.

gym-decision-trees

Simple continuous-states mdp generator for which the optimal policy is a decision tree of given depth. Interface with openAI Gym.

ibmdp-py

Implementation of Iterative Bounding Markov Decision Processes (Topin et. al. 2021)

interpreter-py

Implementation of Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning (Kohler, Delfosse, et. al. 2024).

LunarLander-v2

Using Stable-Baselines 3 library to train a LunarLander-v2 agent. With Yannis Elrharbi-Fleury : https://github.com/sohio92

MorrisPool-ReinforcementLearning

Code and PDF report about reproducing the Morris Pool experiment: model rats behaviour in a pool using reinforcement learning

teachings

Some exercises for the class of Reinforcement Learning at University of Lille

Tree-MBPO

Study Model-Based Policy Optimization by varying the model estimator classes (e.g Decision Trees vs MLP)

KohlerHECTOR/interpreter-py

Implementation of Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning (Kohler, Delfosse, et. al. 2024).

KohlerHECTOR/LunarLander-v2

Using Stable-Baselines 3 library to train a LunarLander-v2 agent. With Yannis Elrharbi-Fleury : https://github.com/sohio92

KohlerHECTOR/aeirl-pytorch

A simple implementation of Auto-Encoding Inverse Reinforcement Learning with PyTorch

KohlerHECTOR/Tree-MBPO

Study Model-Based Policy Optimization by varying the model estimator classes (e.g Decision Trees vs MLP)

KohlerHECTOR/gym-decision-trees

Simple continuous-states mdp generator for which the optimal policy is a decision tree of given depth. Interface with openAI Gym.

KohlerHECTOR/ibmdp-py

Implementation of Iterative Bounding Markov Decision Processes (Topin et. al. 2021)

KohlerHECTOR/MorrisPool-ReinforcementLearning

Code and PDF report about reproducing the Morris Pool experiment: model rats behaviour in a pool using reinforcement learning

KohlerHECTOR/Bayesian-network-learning

Comparing learning algorithms based on constraints (in progress).

KohlerHECTOR/CrossEntropyMethod-VS-PolicyGradient

Simple library based on https://github.com/osigaud/Basic-Policy-Gradient-Labs made for the Master's project: Comparison of Evolutionnary Methods and Reinforcement Learning methods on classical control benchmarks. Supervised by Prof Olivier Sigaud with Damien Legros.

KohlerHECTOR/DPDTreeEstimator

A new tree-based sklearn estimator

KohlerHECTOR/High-Dim-Covariance-Matrix-Estimation

A small library to study some Covariance Matrix Estimators in R. Designed in 2019 as part of my Bachelor's Degree thesis.

KohlerHECTOR/homepage

KohlerHECTOR/MarioNette-pong

Trying MarioNette on Pong

KohlerHECTOR/Pareto-Local-Search

PLS algo for knapsack problem.

KohlerHECTOR/Prioritized-experience-replay

Implementation of Dyna-Q according to Sutton and Barto. Implementation of Mattar's learning model: https://www.nature.com/articles/s41593-018-0232-z

KohlerHECTOR/Segment-Anything-Gym-Wrapper

A gymnasium wrapper for objects states detected with the Segment Anything Model.

KohlerHECTOR/TREX-Tree-Reward-EXploration

Using Tree estimators of the MDP models to then count leaves grouping similar transitions and do count-based exploration.

KohlerHECTOR/asym-rlpo

Asymmetric methods for partially observable reinforcement learning

KohlerHECTOR/teachings

Some exercises for the class of Reinforcement Learning at University of Lille

KohlerHECTOR/centrale-sdm-23-24

Sequential Decision Making in Central, based on RLSS 2019

KohlerHECTOR/Forecasting-RNN

A simple time series forecasting library using RNNs

KohlerHECTOR/MNIST-DeepLearning

Code image classification of MNIST dataset using different architectures: simple linear NN, autoencoder, and highway network

KohlerHECTOR/primenet

Predicting prime numbers as list of bits.

KohlerHECTOR/rlberry

An easy-to-use reinforcement learning library for research and education.

KohlerHECTOR/scikit-learn

scikit-learn: machine learning in Python

KohlerHECTOR/stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

KohlerHECTOR/template_rl_experiment

KohlerHECTOR/trees-programs-videos-iqdagger

KohlerHECTOR/tuto-interpreter