A LoRa simulator with applied multi-armed bandit algorithms.
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Updated
Nov 8, 2021 - C
A LoRa simulator with applied multi-armed bandit algorithms.
Bayesian active learning algorithm with Thompson sampling on multi-armed bandit with Numpy
Repository for the Reinforcement Learning (CSE564) Fall'19 course at IIIT Delhi
Assignments for CS747 - Foundations of Intelligent and Learning Agents
Implementation of multi-armed bandits from scratch
This Repository contain the Answers of "Coursera RL Specialization" Course exercises
A multi-armed bandit implementation in python
CS420: Reinforcement Learning
a C framework including Multi-player Multi-armed bandit (MP-MAB) algorithms applied to IoT network and a LoRa network simulator
Development of algorithms for reinforcement learning. Specifically, software implementation of the algorithms and policies described in the paper Batched Multi-armed Bandits Problems, by Zijun Gao, Yanjun Han, Zhimei Ren, Zhengqing Zhou.
unRL (AKA "unreal") is a set of libraries providing Reinforcement Learning algorithms implemented in PyTorch or Jax.
Multi Armed Bandits implementation using the Jester Dataset
Analysis of various multi armed bandit algorithms over normal and heavy-tailed distributions.
A repository covering a range of topics from multi-arm bandits to reinforcement learning algorithms. Check out different applications of bandits, MDPs and RL algorithms along with theoretical aspects.
Simple Thompson Sampler for a multi-armed bandit problem
A simple repository to highlight and explain Reinforcement Learning topics and concepts
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