Categories: AI/ML Research

Principles of Reinforcement Learning: An Introduction with Python

Reinforcement Learning (RL) is a type of machine learning. It trains an agent to make decisions by interacting with an environment. This article covers the basic concepts of RL. These include states, actions, rewards, policies, and the Markov Decision Process (MDP). By the end, you will understand how RL works. You will also learn how […]

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5 Groundbreaking Applications of Reinforcement Learning in 2024

Reinforcement Learning (RL) has emerged as a powerful paradigm in artificial intelligence, enabling machines to learn optimal behavior through interaction with their environment. In RL, an agent learns to make decisions by performing actions and receiving rewards or penalties, ultimately aiming to maximize cumulative rewards over time. This approach has…

August 29, 2024

In "AI/ML Research"

5 Free Courses on Reinforcement Learning

Reinforcement learning (RL) is a subfield of machine learning where an agent learns to make decisions by interacting with its environment rather than relying solely on pre-existing data. It is an area that blends trial-and-error learning with feedback from actions to improve future performance. In this blog, we will explore…

June 18, 2024

In "AI/ML Research"

Safe Real-World Reinforcement Learning for Mobile Agent Obstacle Avoidance

Collision avoidance is key for mobile robots and agents to operate safely in the real world. In this work, we present an efficient and effective collision avoidance system that combines real-world reinforcement learning (RL), search-based online trajectory planning, and automatic emergency intervention, e.g. automatic emergency braking (AEB). The goal of…

October 12, 2022

In "FAANG"

AI Generated Robotic Content