Title: Dynamic Difficulty Adjustment on MOBA Games,
Abstract: This paper addresses the dynamic difficulty adjustment on MOBA games as a way
to improve the player's entertainment. Although MOBA is currently one of the
most played genres around the world, it is known as a game that offer less
autonomy, more challenges and consequently more frustration. Due to these
characteristics, the use of a mechanism that performs the difficulty balance
dynamically seems to be an interesting alternative to minimize and/or avoid
that players experience such frustrations. In this sense, this paper presents a
dynamic difficulty adjustment mechanism for MOBA games. The main idea is to
create a computer controlled opponent that adapts dynamically to the player
performance, trying to offer to the player a better game experience. This is
done by evaluating the performance of the player using a metric based on some
game features and switching the difficulty of the opponent's artificial
intelligence behavior accordingly. Quantitative and qualitative experiments
were performed and the results showed that the system is capable of adapting
dynamically to the opponent's skills. In spite of that, the qualitative
experiments with users showed that the player's expertise has a greater
influence on the perception of the difficulty level and dynamic adaptation.