March 26, 2020
4 min read

Reinforcement Learning – What Distinguishes a Real AI from The Wannabes

Clearly defining the construct of artificial intelligence is difficult, if only because the term intelligence alone can hardly be clearly defined. That's why AI is frequently used as a buzzword. However, there are some very decisive technological nuances that make the difference, especially in economic terms.    

Machine Learning is the generic term for various processes that can be used within an artificial system. Machine learning in itself means that an artificial system is capable of analyzing data and uncovering patterns or regularities within the data. Based on this, the system can also evaluate unknown data. But this kind of machine learning is still far from being an AI.

Artificial intelligence starts when an artificial system is able to adapt to changes in its environment and to develop itself accordingly. This is where reinforcement learning comes into play.

Reinforcement Learning - a subdomain of machine learning - is a very powerful algorithmic procedure and describes the concept of self-enhancing learning. This means that this type of learning is always linked to a very concrete goal, which is approached step by step. Every single learning step is checked and evaluated: if it serves to achieve the goal, it is rewarded. A system that develops itself in this way learns to "think" economically. In doing so, it continuously adapts to the given environmental conditions in such a way that it achieves specified goals.

What does this have to do with Dynamic Pricing? Especially in dynamic price optimization, it’s important to rely on an AI that develops itself further through reinforcement learning. Because for you, this means that you actively control the algorithm from the outset. You specify the economic goal (such as sales, turnover, profit or margin) and the procedure then learns a strategy for your individual business through which the KPIs you have specified are best achieved. Because your target is also the reward value for the AI, the process will constantly evolve to ensure that your target KPIs are met at all times - even when environmental conditions change (inventory, demand, competition, etc.).

If you have not yet worked with AI because these approaches seem like a black box that you cannot master – think again. Retailers are now able to easily set a global strategy and concrete goals - the AI does all the work.

If you’re curious as to how this affects your day-to-day, feel free to reach out.