Importance Sampling in Reinforcement Learning

5 mins read Motivation Importance sampling plays a key role in sampling inferencing and reinforcement learning RL. In RL, importance sampling estimates the […]

REINFORCE Algorithm explained in Policy-Gradient based methods with Python Code

17 mins read Policy gradients Policy gradients is a family of algorithms for solving reinforcement learning problems by directly optimizing the policy in […]

Deep Reinforcement Learning: Using policy-based methods to play Pong from pixels

34 mins read This is a long-overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that computers can […]

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

16 mins read Evolution strategies (ES) is an optimization technique that’s been known for decades, rivals the performance of standard reinforcement learning (RL) techniques on […]

Double DQN and Dueling DQN in Reinforcement Learning

9 mins read In this part, we will see two algorithms that improve upon DQN. These are named Double DQN and Dueling DQN. But first, let’s […]

SumTree data structure for Prioritized Experience Replay (PER) explained with Python Code

14 mins read Weighted sampling from a list-like collection is an important activity in many applications. Weighted sampling involves selecting samples randomly from […]

Improvements in Deep Q-Learning with Python code: Dueling Double DQN, Prioritized Experience Replay, and Fixed Q-targets

28 mins read Deep Q-Learning was introduced in 2014. Since then, a lot of improvements have been made. So, today we’ll see four […]

Upper Confidence Bound (UCB) Algorithm Explained with Python code

7 mins read In this tutorial, I will explain to you the application of the Upper Confidence Bound(UCB) algorithm to solve the Multi […]

Difference between model-based and model-free reinforcement learning

3 mins read To answer this question, let’s revisit the components of an MDP, the most typical decision-making framework for RL. An MDP […]

Understand Q-Learning in Reinforcement Learning with a numerical example and Python implementation

14 mins read This tutorial introduces the concept of Q-learning through a simple but comprehensive numerical example.  The example describes an agent which […]

What is q-learning?

5 mins read Introduction One of my favorite algorithms that I learned while taking a reinforcement learning course was q-learning. Probably because it […]