Pinned Repositories
Bandit-and-Reinforcement-Learning
Python implementation for Reinforcement Learning algorithms -- Bandit algorithms, MDP, Dynamic Programming (value/policy iteration), Model-free Control (off-policy Monte Carlo, Q-learning)
bayesla-link-adaptation
Bayesian Link Adaptation under a BLER Target
CommPy
Digital Communication with Python
decentralized_qlearning_resource_allocation_in_wns
Deep-Reinforcement-Learning-for-Dynamic-Spectrum-Access
Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication
DRL_for_DDBC
Simulation codes for the manuscript "Deep Reinforcement Learning for Distributed Dynamic MISO Downlink-Beamforming Coordination" submitted to IEEE Transactions on Communications
gr-ofdm
Out-of-tree module for GNU Radio containing a complete OFDM implementation including GUI for reasearch and teaching
IoT-MAB
Decentralized Intelligent Resource Allocation for LoRaWAN Networks
ITU-Challenge-ML5G-PHY-RL
Scripts for the "ITU-ML5G-PS-006: ML5G-PHY-Reinforcement learning: scheduling and resource allocation"
mabwiser
[IJAIT 2021] MABWiser: Contextual Multi-Armed Bandits Library
JCK-1096's Repositories
JCK-1096/Bandit-and-Reinforcement-Learning
Python implementation for Reinforcement Learning algorithms -- Bandit algorithms, MDP, Dynamic Programming (value/policy iteration), Model-free Control (off-policy Monte Carlo, Q-learning)
JCK-1096/CommPy
Digital Communication with Python
JCK-1096/ITU-Challenge-ML5G-PHY-RL
Scripts for the "ITU-ML5G-PS-006: ML5G-PHY-Reinforcement learning: scheduling and resource allocation"
JCK-1096/mabwiser
[IJAIT 2021] MABWiser: Contextual Multi-Armed Bandits Library
JCK-1096/MARLforChannelBondingWLANs
WLAN channel access through Multi-Agent Reinforcement Learning (MARL)
JCK-1096/MP-MAB
This project is created for the simulations of the paper: [Wang2021] Wenbo Wang, Amir Leshem, Dusit Niyato and Zhu Han, "Decentralized Learning for Channel Allocation inIoT Networks over Unlicensed Bandwidth as aContextual Multi-player Multi-armed Bandit Game", to appear in IEEE Transactions on Wireless Communications, 2021.
JCK-1096/PythonExamples
Python coding examples for wireless communication systems. This includes currently the topics of modulation such as 4-QAM, BPSK (2-PSK) with an AWGN channel and also Rayleigh fading.
JCK-1096/aima-python
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
JCK-1096/algossim
This repository aims at learning most popular MAB and CMAB algorithms and watch how they run. It is interesting for those wishing to start learning these topics.
JCK-1096/Bayesian-Statistics
Course material for Bayesian and Modern Statistics, STA601, Duke University, Spring 2015.
JCK-1096/Communication_Modulation
This repository provides a simple python script for getting experience with common modulation techniques i.e. QAM, PSK, ASK and BPSK
JCK-1096/contextual_MAB
A simple pure-python framework for dealing with the contextual multi-armed bandit problems
JCK-1096/Deep-Reinforcement-Learning-Algorithms
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
JCK-1096/gnuradio
GNU Radio – the Free and Open Software Radio Ecosystem
JCK-1096/gym
A toolkit for developing and comparing reinforcement learning algorithms.
JCK-1096/highway-env
A minimalist environment for decision-making in autonomous driving
JCK-1096/komm
An open-source library for Python 3 providing tools for analysis and simulation of analog and digital communication systems.
JCK-1096/leetcode
LeetCode solutions.
JCK-1096/Leetcode-1
🎓Leetcode solutions in Python 📚
JCK-1096/leetcode-_-C_solutions
My leetcode solutions in C
JCK-1096/Machine-Learning-Andrew-Ng
Full Notes of Andrew Ng's Coursera Machine Learning.
JCK-1096/machine_learning_examples
A collection of machine learning examples and tutorials.
JCK-1096/multiagent-particle-envs
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
JCK-1096/Paper-with-Code-of-Wireless-communication-Based-on-DL
无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL
JCK-1096/pyphysim
Simulation of Digital Communication (physical layer) in Python.
JCK-1096/Python-for-Algorithms--Data-Structures--and-Interviews
Files for Udemy Course on Algorithms and Data Structures
JCK-1096/reinforcement-learning-an-introduction
Solutions to exercises in Reinforcement Learning: An Introduction (2nd Edition).
JCK-1096/reinforcement-learning-an-introduction-1
Python Implementation of Reinforcement Learning: An Introduction
JCK-1096/riscv-tests
JCK-1096/Scalable_Deep_Reinforcement_Learning_for_Routing_and_Spectrum_Access_in_Physical_Layer
This is the repository containing the codes for the paper "Scalable Deep Reinforcement Learning for Routing and Spectrum Access in Physical Layer"