Expanding exertion gaming

While exertion games - digital games where the outcome is determined by physical exertion - are of growing interest in HCI, we believe the current health and fitness focus in the research of exertion games limits the opportunities this field has to offer. In order to broaden the agenda on exertion games, we link the existing fields of sports and interactive entertainment (arguing these fields have much to offer) by presenting four of our own designs as case studies. Using our experiences with these designs we highlight three key strategies to guide designers in the creation of richer exertion game experiences: designing a temporal trajectory through games with reference to the way exertion changes over time, designing for the inevitable and not necessarily negative effects of pain in exertion games, and designing for the highly socially situated nature of exertion gaming

Expanding exertion gaming

While exertion games - digital games where the outcome is determined by physical exertion - are of growing interest in HCI, we believe the current health and fitness focus in the research of exertion games limits the opportunities this field has to offer. In order to broaden the agenda on exertion games, we link the existing fields of sports and interactive entertainment (arguing these fields have much to offer) by presenting four of our own designs as case studies. Using our experiences with these designs we highlight three key strategies to guide designers in the creation of richer exertion game experiences: designing a temporal trajectory through games with reference to the way exertion changes over time, designing for the inevitable and not necessarily negative effects of pain in exertion games, and designing for the highly socially situated nature of exertion gaming

Innovative navigation artificial intelligence for motor racing games

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Masters of Science by ResearchMotor racing games are pushing the boundaries of realism and player experience. Artificial Intelligence (AI) allows developers to create believable opponents. By getting their AI to follow a racing line that is similar to that taken by real racing drivers, developers are able to create a sense that the AI racers are trained drivers. This paper identifies two methods used in the field: the sector based system and the sensor based system. The sector based approach offers two or more predetermined lines for the AI to follow, with added logic allowing the AI to judge when to switch between lines. The sensor method is able to guide AI vehicles around tracks with sensors, offering more possible behaviours and lines. After implementation, the strengths and weaknesses of both methods are realised. The planning and development of a hybrid system was based on these findings. The resulting system is able to produce a more believable line for the AI. With the setting up process of a race track the sector method taking a long time, exploration into tool development is conducted to reduce the process. The subsequent tool reduced the time needed to set up a track, providing results similar to the old method