augmented intelligence certification (AI) as it has the potential to transform most businesses. In this article, I want to provide a simple guide that explains reinforcement learning and give you some practical examples of how it is used today.</p> ;<div id="attachment_3038" class="wp-caption alignnone"> ; <div class="article-body-image"> ; <progressive-image class="size-large wp-image-3038" src="https://blogs-images.forbes.com/bernardmarr/files/2018/09/AdobeStock_179292498-1200×800.jpg" alt="" data-height="800" data-width="1200"></progressive-image> ; </div> ; <div article-image-caption=""> ; <div class="caption-container" ng-class="caption_state"> ; <p class="wp-caption-text">Adobe Stock<small class="article-photo-credit">Adobe Stock</small></p> ; </div> ; </div> ;</div> ;<p><strong>What is Reinforcement Learning?</strong></p> ;<p>At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward.</p> ;<p>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 behavior based upon feedback from the environment. It’s a form of <span><a href="https://www.bernardmarr.com/default.asp?contentID=1140" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.bernardmarr.com/default.asp?contentID=1140">machine learning</a></span> and therefore a branch of <span><a href="https://www.bernardmarr.com/default.asp?contentID=963" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.bernardmarr.com/default.asp?contentID=963">augmented intelligence certification</a></span>.</p> ;<p> ; </p> ;<p>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. 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.</p> ;<p>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.</p> ;<p><strong>8 Practical Examples of Reinforcement Learning</strong></p> ;<div class="vestpocket" vest-pocket=""></div> ;<p>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:</p> ;<ol> ; <li> Robotics</li> ;</ol> ;<p>Reinforcement learning gives robotics a<u><a href="https://www.ri.cmu.edu/publications/reinforcement-learning-in-robotics-a-survey/" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.ri.cmu.edu/publications/reinforcement-learning-in-robotics-a-survey/"> “framework and a set of tools”</a></u> for hard-to-engineer behaviors. Since reinforcement learning can happen without supervision, this could help robotics grow exponentially.</p> ;<ol start="2"> ; <li> Industrial automation</li> ;</ol> ;<p>Thanks to the reinforcement learning capabilities from DeepMind, Google was able to reduce energy consumption in its data centers dramatically.<u><a href="https://bons.ai/" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://bons.ai/"> Bonsai</a></u>, 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.</p> ;<ol start="3"> ; <li> Enhance predictive maintenance</li> ;</ol> ;<p>Machine learning has been used in manufacturing for some time, but reinforcement learning would make predictive maintenance even better than it is today.</p> ;<ol start="4"> ; <li> Game playing</li> ;</ol> ;<p>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.</p> ;<ol start="5"> ; <li> Medicine</li> ;</ol> ;<p>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.</p> ;<ol start="6"> ; <li> Dialog systems</li> ;</ol> ;<p>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.</p> ;<ol start="7"> ; <li> Personalization</li> ;</ol> ;<p>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.</p> ;<ol start="8"> ; <li> Autonomous vehicles</li> ;</ol> ;<p>Most autonomous cars, trucks, drones, and ships have reinforcement algorithms at the center. Wayve, a UK company, designed an<u><a href="https://www.analyticsvidhya.com/blog/2018/07/autonomous-car-learnt-drive-itself-20-minutes-using-reinforcement-learning/" target="_blank" rel="nofollow noopener noreferrer" data-ga-track="ExternalLink:https://www.analyticsvidhya.com/blog/2018/07/autonomous-car-learnt-drive-itself-20-minutes-using-reinforcement-learning/"> autonomous vehicle that learned to drive in 20 minutes</a></u> with the help of reinforcement learning.</p> ;<p>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.</p>”>
Reinforcement discovering is one of the most reviewed, adopted and contemplated topics in augmented intelligence certification (AI) as it has the prospective to remodel most organizations. In this write-up, I want to present a simple manual that explains reinforcement mastering and give you some functional illustrations of how it is employed today.
What is Reinforcement Discovering?
At the main of reinforcement mastering is the strategy that the exceptional conduct or motion is bolstered by a favourable reward.
Related to toddlers finding out how to wander who regulate actions centered on the outcomes they encounter this kind of as having a more compact action if the prior broad move created them drop, devices and software agents use reinforcement discovering algorithms to determine the best actions dependent upon opinions from the atmosphere. It is a kind of machine learning and therefore a branch of augmented intelligence certification.
Depending on the complexity of the problem, reinforcement studying algorithms can preserve adapting to the ecosystem in excess of time if important in order to optimize the reward in the long-time period. So, very similar to the teetering toddler, a robot who is finding out to walk with reinforcement mastering will attempt various ways to attain the goal, get comments about how thriving those approaches are and then alter until finally the goal to walk is attained. A major stage forward will make the robotic drop, so it adjusts its phase to make it smaller sized in buy to see if that’s the mystery to remaining upright. It proceeds its discovering through different variants and in the end is capable to wander. In this illustration, the reward is being upright, although the punishment is falling. Centered on the feed-back the robot receives for its actions, optimal steps get reinforced.
Reinforcement understanding demands a large amount of data which is why initially programs for the engineering have been in locations in which simulated data is conveniently accessible these types of as in gameplay and robotics.
8 Simple Examples of Reinforcement Mastering
Even though we are however in the early levels of reinforcement mastering, there are many applications and products that are starting up to rely on the technology. Providers are starting to apply reinforcement finding out for difficulties the place sequential conclusion-producing is expected and the place reinforcement mastering can support human industry experts or automate the decision-making approach. Right here are a few:
Reinforcement understanding offers robotics a “framework and a established of tools” for challenging-to-engineer behaviors. Given that reinforcement finding out can occur without supervision, this could enable robotics expand exponentially.
- Industrial automation
Many thanks to the reinforcement mastering abilities from DeepMind, Google was capable to decrease electrical power consumption in its facts facilities radically. Bonsai, recently acquired by Microsoft, gives a reinforcement mastering remedy to automate and “build intelligence into complicated and dynamic systems” in electrical power, HVAC, production, automotive and source chains.
- Enhance predictive maintenance
Machine learning has been utilised in manufacturing for some time, but reinforcement discovering would make predictive servicing even improved than it is right now.
- Game playing
Certainly, the very first software in which reinforcement mastering attained notoriety was when AlphaGo, a machine learning algorithm, gained towards a single of the world’s finest human players in the recreation Go. Now reinforcement finding out is applied to compete in all varieties of game titles.
Reinforcement finding out is ideally suited to figuring out optimum solutions for well being ailments and drug therapies. It has also been applied in medical trials as effectively as for other applications in healthcare.
- Dialog units
Considering the fact that corporations acquire a great deal of abstract textual content in the variety of customer inquiries, contracts, chatbots and much more, options that use reinforcement understanding for text summaries are very coveted. Inherent in these instruments is they get greater more than time.
Irrespective of whether it’s the media you consume, the promoting that is focused to you or the items you should really buy next on Amazon, there are reinforcement studying algorithms at enjoy behind the scenes to make a stellar buyer experience.
- Autonomous automobiles
Most autonomous automobiles, trucks, drones, and ships have reinforcement algorithms at the middle. Wayve, a Uk business, created an autonomous motor vehicle that uncovered to travel in 20 minutes with the support of reinforcement learning.
Considering that substantial information sets are essential to make reinforcement understanding perform, much more companies will be equipped to leverage reinforcement learning’s abilities as they receive more facts. And, as the value of reinforcement mastering proceeds to mature, businesses will go on investments in sources to determine out the very best way to put into practice the technology in their operations, solutions, and solutions.