Understanding player psychology and predicting player actions
The purpose of this research is to gain a better understanding of gamer’s mindset and to predict its next actions in a game. Being able to anticipate the player’s next move can lead to improvements in the overall user performance as well as in its engagement in the game.
Current related work includes next moves and goal recognition in open-ended serious games. This is used to assess players’ learning process and to enhance their experiences. Considerable improvements have been experienced in mobile cloud games from predicting the player’s behaviour based on low-level actions from the virtual environment. This helped to reduce the delay by masking the network latency.
Understanding the player’s mindset and predicting the next moves could improve the Virtual Reality games. The field of VR has started to gain more and more commercial interest, consequently, the desire of experiencing VR at home has increased. Several limiting factors are the spacious environment and the complex kit needed for an immersive experience. One possible way to overcome this problem would be to reduce the magnitude of physical movement required by the player. The user’s actions could be predicted by applying a combination of data mining and machine learning techniques; with this information, the game could pre-emptively update the position of the player’s character in the game world.
My previous academic background consists of a Mathematics and Computer Science Baccalaureate Diploma and a Computer Science Undergraduate Degree. In my home country, I undertook a 4-year High School/College specialisation in Mathematics and Computer Science. Apart from Maths and Computer Science, I also studied Logic, Physics and other science related modules. In my undergraduate programme in Goldsmiths, I was introduced to fundamentals of Computer Science as well as to various technics of analysing and extracting information from data. In my final year, I studied Machine Learning, Natural Computing and Data Mining. I was also engaged in an exciting work as part of my final year project that involved data gathering and analysation using Natural Language Processing and Machine Learning techniques.
During my undergraduate studies, I’ve had various part-time and temporary jobs. I’ve taught kids creative coding, developed software and provided IT-focused customer support.
Home institution: Goldsmiths
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