If a game is to be truly compelling, then it needs to be balanced. But the way this is done, thanks to the ongoing revolution in AI and machine learning, is changing fundamentally. Let’s take a closer look at this phenomenon.
What Is Game Balancing and Why It Matters
What does it mean for a game to be balanced. The answer might seem straightforward. A good game is carefully calibrated. Not too tricky that it becomes frustrating, and yet not so easy that it becomes boring. The various elements will need to be weighed carefully to prevent any one of them from dominating, too – just think about how boring chess would be if the queen were capable of jumping over other pieces.
How Machine Learning Automates Balance Adjustments
Traditionally, attaining the right balance involves a great deal of trial and error. A game is played, adjusted, and replayed, with feedback being issued from a team of testers, over many iterations.
While there remains a role for this kind of manual testing, it can now be supplemented by machine learning algorithms that can pore through gameplay data, or even simulate new gameplay, and automatically test adjustments on the fly. This might even allow for the action to be adjusted on a per-system basis, as it’s unfolding.
Personalised Difficulty and Player Retention
The right fine-tuning machine learning algorithm might consider the skill of the player, and adjust the difficulty of a game accordingly. It might spot that a given player has difficulty with a given mechanic, like jumping, and then dynamically reduce the need for jumping. This can keep the player engaged for longer, and prevent them from quitting out of frustration.
Enhancing Mobile Casino Experiences with ML
A mobile casino experience is particularly suited to machine-learning improvements. And these might extend beyond the actual gameplay. When you’re gambling, it’s important that the odds remain predictable, which means that dynamic difficulty adjustments might be off the table.
On the other hand, other elements of the experience might be improved through machine learning. It might be used to make better, more personalised suggestions for new games, or to spot when a player is at risk. Early intervention can often make a big difference in preventing problem gambling, and machine learning allows for it to be done in a personalised way that doesn’t rely on fixed metrics like time played or money wagered.
