2019-08-23, 13:30–13:45, Central Library Theatrette 1
Intelligent systems are becoming increasingly ubiquitous and invisible. Designers can employ smart systems in order to improve user experiences. For example, in games, players experience frustration when faced with a challenge that is too difficult, but quickly become bored if the challenge is too easy. Yet, the notion of what is difficult or easy is relative to the player’s skill level.
To address this, game designers can employ dynamic difficulty adjustment (DDA) to cater to a wider range of skill levels. Unlike traditional designs offering discrete levels of difficulty, DDA systems allow for difficulty adjustment in games “on-the-go”, without interruption - even while the player is in the middle of playing the game. However, much of existing research on DDA focus on the creation of adjustment systems that are autonomous and automatic.
Typically, these computational systems are designed to observe and record measures of player performance, be it via game heuristics or other forms of heuristics such as psychophysiological feedback. These measures are used to adjust the game difficulty to an appropriate level. Ironically, such approaches tend not to consider the players’ agency despite being applied on a medium known for a vast spectrum of interactivity.
By exploring the design of DDA systems with the approach of giving consideration to what the player can do (or in some cases, not do) to influence such systems allows for a fresh perspective to designing game systems. This approach can be extended design smart systems in practical, real world scenarios.