Reinforcement learning is a branch of artificial intelligence where agents learn optimal behaviors through positive rewards, similar to how toddlers learn to walk. Its applications are expanding in various fields such as robotics, healthcare, and personalized services, leveraging large datasets for continuous improvement. As the technology matures, companies are increasingly investing in reinforcement learning to enhance decision-making processes across industries.

1. Artificial Intelligence:
What Is Reinforcement Learning?
A Simple Explanation And
8 Practical Examples

2. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Title
Text
IntroductionIntroduction
Artificial Intelligence:
What Is Reinforcement Learning?
Reinforcement learning is one of the most discussed, followed and contemplated
topics in artificial intelligence (AI) as it has the potential to transform most
businesses.
In this presentation, I want to provide a simple guide that explains reinforcement
learning and give you some practical examples of how it is used today.

3. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
What Is Reinforcement Learning?
At the core of reinforcement learning is the concept that the optimal behaviour or
action is reinforced by a positive reward.
Similar to toddlers learning how to walk who adjust actions based on the
outcomes they experience such as taking a smaller step if the previous broad step
made them fall, machines and software agents use reinforcement learning
algorithms to determine the ideal behaviour based upon feedback from the
environment. It’s a form of machine learning and therefore a branch of artificial
intelligence.
Depending on the complexity of the problem, reinforcement learning algorithms
can keep adapting to the environment over time if necessary in order to maximize
the reward in the long-term.

4. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
What Is Reinforcement Learning?
So, similar to the teetering toddler, a robot who is learning to walk with
reinforcement learning will try different ways to achieve the objective, get
feedback about how successful those ways are and then adjust until the aim to
walk is achieved. A big step forward makes the robot fall, so it adjusts its step to
make it smaller in order to see if that's the secret to staying upright. It continues
its learning through different variations and ultimately is able to walk. In this
example, the reward is staying upright, while the punishment is falling. Based on
the feedback the robot receives for its actions, optimal actions get reinforced.
Reinforcement learning requires a lot of data which is why first applications for the
technology have been in areas where simulated data is readily available such as in
gameplay and robotics.

5. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
8 Practical Examples of
Reinforcement Learning
Even though we are still in the early stages of reinforcement learning, there are
several applications and products that are starting to rely on the technology.
Companies are beginning to implement reinforcement learning for problems
where sequential decision-making is required and where reinforcement learning
can support human experts or automate the decision-making process.
Here are a few:

6. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Reinforcement learning gives robotics a “framework and a set of
tools” for hard-to-engineer behaviours. Since reinforcement
learning can happen without supervision, this could help
robotics grow exponentially.
Robotics
Industrial Automation
Thanks to the reinforcement learning capabilities from
DeepMind, Google was able to reduce energy consumption in
its data centers dramatically. Bonsai, recently acquired by
Microsoft, offers a reinforcement learning solution to automate
and “build intelligence into complex and dynamic systems” in
energy, HVAC, manufacturing, automotive and supply chains.

7. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Machine learning has been used in manufacturing for some
time, but reinforcement learning would make predictive
maintenance even better than it is today.
Enhance Predictive Maintenance
Game Playing
Indeed, the first application in which reinforcement learning
gained notoriety was when AlphaGo, a machine learning
algorithm, won against one of the world’s best human players in
the game Go. Now reinforcement learning is used to compete in
all kinds of games.

8. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Reinforcement learning is ideally suited to figuring out optimal
treatments for health conditions and drug therapies. It has also
been used in clinical trials as well as for other applications in
healthcare.
Medicine
Dialogue Systems
Since companies receive a lot of abstract text in the form of
customer inquiries, contracts, chatbots and more, solutions that
use reinforcement learning for text summaries are highly
coveted. Inherent in these tools is they get better over time.

9. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Whether it’s the media you consume, the advertising that’s
targeted to you or the goods you should purchase next on
Amazon, there are reinforcement learning algorithms at play
behind the scenes to create a stellar customer experience.
Personalisation
Autonomous Vehicles
Most autonomous cars, trucks, drones, and ships have
reinforcement algorithms at the centre. Wayve, a UK company,
designed an autonomous vehicle that learned to drive in 20
minutes with the help of reinforcement learning.

10. © 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Since significant data sets are required to make reinforcement learning work,
more companies will be able to leverage reinforcement learning's capabilities as
they acquire more data.
And, as the value of reinforcement learning continues to grow, companies will
continue investments in resources to figure out the best way to implement the
technology in their operations, services, and products.

11. © 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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