Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - INTERCOGAM (Information Theoretic Evaluation of Random Content Generation in Games)

Teaser

INTERCOGAM’s goal is to develop and use information theory based intrinsic motivation formalisms to evaluate automatically generated game mechanics. Content generation is one of the production bottlenecks of professional game design, which has begun to be addressed by...

Summary

INTERCOGAM’s goal is to develop and use information theory based intrinsic motivation formalisms to evaluate automatically generated game mechanics. Content generation is one of the production bottlenecks of professional game design, which has begun to be addressed by procedural content generation. In this field, search based procedural content generation uses the idea of evolutionary algorithms to represent, modify and adapt games and game content to maximise fun and engagement with the game. One major challenge here is the identification of widely applicable fitness functions, which capture the different aspects of what makes a game fun, such as challenge level, complexity, pacing, etc. INTERCOGAM will relate psychological and game design concepts of game experience to either existing formalisms for intrinsic motivation or develop new ones, where appropriate. Human play testers will then play procedurally generated games and evaluate their own experience, allowing us to verify whether our formalism captures the actual human motivation, and whether humans indeed act according to certain intrinsic motivations. INTERCOGAM will yield both, a tool to generate new and engaging game ideas, aiding better and faster game design, and provide new insights into how the human mind engages with different worlds where there is no external reward present.

Work performed

The INTERCOGAM project so far looked at a range of games and game-like frameworks and applied different intrinsic motivation frameworks and other artificial intelligence tools to generate interesting behaviour and make interesting game content.
Particularly noteworthy is the development of the coupled empowerment framework – where a non-player character is imbued with a set of motivations that cause it to act in an antagonistic or helpful way. The strength of this approach is its flexibility and robustness – which makes it applicable to a range of different games without much adaptation. We demonstrated that this framework captures relatively intuitive notions of support or antagonism, and thus provides us with formal building block to build companion or non-player behaviour. We also argued, and showed in simulation, that this approach could be a feasible way to provide some basic ethical framework to robots, giving them basic notion for empowering humans, maintaining their own ability to act and maintaining their operational flexibility.

As part of the development of the coupled empowerment framework we also made several improvements towards more efficient ways of computing empowerment – specifically for discrete and deterministic scenarios. This lower computational load makes it more feasible to apply empowerment to a range of scenarios.

The INTERCOGAM project also contributed to the further development of the theory behind intrinsic motivations. We developed the philosophical argument that aims to close the gap between basic assumptions about the mind from an enactive perspective to the development of a mathematical formalism. Furthermore, we also partook in the development of a unifying framework that can express a range of different intrinsic motivation – making it possible to compare these different notions formally and in a simulation. While games offer a great testbed to evaluate and benefit from robust intrinsic motivation models, understanding intrinsic motivation better offers us great insights on how minds operate and how to approach problems in general.

Final results

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.

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.

Website & more info

More info: http://homepages.herts.ac.uk/.