by Apoorva Bellapu
Apr 2, 2022
Reinforcement learning (RL) has become hugely popular since its inception. Because it provides the opportunity to train the machine learning (ML) models, to make better decisions, organizations rely on reinforcement learning like never before. RL has delivered results that have changed the dynamics of several sectors for the better. That said, let’s take a look at the top 10 real-life applications of enhanced learning in 2022.
Reinforcement learning is widely used in healthcare. One such area is that of a dynamic treatment regimen that can reduce or eliminate the delayed impact of treatments through multi-objective healthcare optimization solutions. Well, that’s not all – through RL it is also possible for the doctors to discover the type of treatment, the right doses of drugs and timings for taking doses.
Be it adventure, mystery or action, gaming in these areas has left no stone unturned to grab eyeballs. All your favorite games can now see improved performance as a result of RL. In addition, it is also possible to optimize your favorite games. Wondering how? Well, that’s just by applying appropriate prediction models through RL-enabled strategies.
Trading is one of the hottest sectors growing in popularity every day. The main goal behind trading is to get good returns. This is exactly where reinforcement learning comes into play. RL and machine learning algorithms help drive better returns and strengthening learning-based financial systems can further optimize equity returns.
With reinforcement learning, organizations have deployed their own RL systems for both packaging and quality testing. This has helped them achieve their business goals faster and more efficiently than ever before.
Who would deny that e-commerce is one of the fastest growing industries? Considering how important customer satisfaction is when it comes to e-commerce, RL helps provide customization in choices to their liking.
Strong marketing is one of the main drivers for the growth of the company. Well, reinforcement learning is no less than a savior here. It helps track customer satisfaction points that create huge data sets that can be beneficial for profitable marketing strategies.
Who would have ever thought that there would ever be a machine that would perform tasks just like a human being? Well, technology undoubtedly works wonders! Training a robot to be able to make decisions (like humans) has become easier than ever – thanks to reinforcement learning.
Reduction of energy consumption
Reinforcement learning helps predict how different combinations will affect future energy consumption. This is followed by identifying actions that will lead to minimum power consumption while maintaining a set standard of safety criteria. How great is that?
RL has made it very easy to recommend news that fits the frequently changing preferences of readers and/or users. This is because journalists can now be equipped with an RL-based system that monitors both intuitive news content and headlines.
Many countries have already welcomed self-driving cars. The success behind this goes to reinforcement learning and deep learning. Various factors such as trajectory optimization, motion planning, dynamic path, controller optimization, and highway scenario-based learning policies, just to name a few, are all taken into consideration and implemented successfully as a result of RL.
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