For centuries, card games have been popular and addictive entertainment. Various types of card games have been gradually introduced, and different games have earned followings of their own. But what exactly makes these games addictive? Scientists have tried to delve into this mystery.
Addictive Value
SciTechDaily reports that the researchers used the motion-in-mind model, AI stimulations, and game refinement to learn more about such a phenomenon.
Phenomena known as jerks play a role in this. A jerk refers to a sudden acceleration measurement that is common across sports science, engineering, manufacturing, and others. Researchers suggest that looking into jerk impact can also shed light on gameplay.
The theory of game refinement shows that acceleration serves as a representative of the balance between a game's uncertainty and certainty. The balance is dubbed the GR, or game refinement value, and serves as the key indicator of how engaged a player is.
The motion-in-mind model is yet another perspective to take into account. It looks at the level of uncertainty in a game's progress relative to two specific measures: mass and velocity. Mass refers to how difficult it is to win, and velocity refers to the win rate. Such values can also translate into psychological reactions of some sort.
A jerk, dubbed AD or addictive, can be seen as surprise or unpredictability. Games that have higher addictive values are full of surprises and unpredictability. This, in turn, makes them addictive.
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What Makes Card Games Addictive?
Researchers looked into how jerks impact game addiction toward various card games. Their study was published in the IEEE Access journal.
According to Eurekalert, assistant professor Mohd. Nor Akmal Klalid of JAIST's (Japan Advanced Institute of Science and Technology) School of Information Science says that card games are the usual games with incomplete information. They have repeatable and short rounds, strategies, and chances to make them entertaining and addictive games. They wanted to see why this was the case.
The specialists looked into the games' design, complexity, and rules through the motion-in-mind model and game refinement theory. Then, they conducted two stimulations with AI agents that played on their own.
In the first one, the AI mirrored a structured game that was played by differently skilled contestants. The second experiment, however, had various games that were played by a set AI level. The observed differences were in difficulty levels and winning odds. The analysis allowed the researchers to compare various card games.
Results revealed that sophistication and skill should match in order to come up with reasonable addictive and game refinement values. Other than that, the games should also be fair and balanced so that winning would not merely be a result of luck or chance.
With their investigation, the researchers distinguished play principles for addictive games. The game progress model's four factors, namely jerk, acceleration, game length, and velocity, all corresponded to reward frequency, reward cost, unpredictability, and uncertainty.
The researchers also looked into game surprise, attractiveness, fairness, and reinforcement.
Professor Khalid concludes that the components show how game refinement and addictive value measures are vital to understanding how gameplay works. They help make games educational and attractive.
Beyond games, the findings can also help other activities become enjoyable, surprising, engaging, and even addictive.
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