INTERCOGAM applied empowerment to complex game scenarios, and was thus able to showcase its robustness beyond previously existing models. This made it viable as a behaviour generation approach, which allowed us to define antagonistic or companion like behaviour on more fundamental principles than before. Extending this further could change the way we generate and think about non-player behaviour generation. Combined with the novel empirical data about human perception of intrinsically motivate behaviour, this demonstrates the feasibility of a novel approach to robust and generic behaviour generation. While many of the approaches and techniques developed in INTERCOGAM still require human evaluation, the existing results are promising, and demonstrate how intrinsically motivated behaviour generation can be used to produce engaging and socially evocative NPCs or robots. This would not only allow for the development of better and more engaging games, but could also provide useful in providing a toolbox for generating robot behaviour. Being able to produce more socially acceptable or socially aware robots would be beneficial to a wide range of HRI applications, including elder care, domestic and service robots, robot therapy, etc.
INTERCOGAM’s other main goal is to provide a metric that can evaluate a range of different games (or experiences) and provide us with a good proxy for the actual experience. Our initial results indicate that an intrinsic motivation-based approach, as advocated by us, could provide us with a metric that actually evaluates the experience of a player with a game (rather than some property of the artefact) across a range of games. This would have major applications, as it would allow game companies to automatically test games without having to hand-craft test for a specific game or scenario.
Our development of the Generative Design for Minecraft competition and the associated framework have also already led to an increased focus on the idea of adaptive procedural content generation. Universities around the world have started to use the GDMC competition as part of their coursework, and this had allowed us to build a community that is interested in various forms of procedural content generation, and their comparison and human evaluation. Noteworthy here is also that the GDMC includes members of the general public as participants and generators of novel ideas, rather than as test subjects – and, as such, its pushes the idea of citizen science further .