H2020Индивидуална стипендия2016–2019

INTERCOGAM · Information Theoretic Evaluation of Random Content Generation in Games

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2016-12-01 → 2019-11-30
Финансиране от ЕС: 251 858 €
Участници: 2
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Автоматичното генериране на игри се анализира чрез теорията на информацията, за да се разбере какво прави нивата или механиките забавни. Това помага за по-бързото създаване на ангажиращи игри и разкрива как човешкият ум взаимодейства с виртуални светове без външни награди.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Information Theoretic Evaluation of Random Content Generation in Games

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 also 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.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

INTERCOGAM’s goal is to develop and use information theory based intrinsic motivation formalisms to evaluateautomatically generated game mechanics. Content generation is one of the production bottlenecks of professional gamedesign, which has begun to be addressed by procedural content generation. In this field, search based procedural contentgeneration uses the idea of evolutionary algorithms to represent, modify and adapt games and game content to maximisefun 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 forintrinsic motivation or develop new ones, where appropriate. Human play testers will then play procedurally generatedgames 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 generatenew and engaging game ideas, aiding better and faster game design, and provide new insights into how the human mindengages with different worlds where there is no external reward present.

Оригинален текст от CORDIS (на английски).

Участници

THE UNIVERSITY OF HERTFORDSHIRE HIGHER EDUCATION CORPORATION · HatfieldКоординаторОбединеното кралство
NEW YORK UNIVERSITY · NEW YORKСъединени щати