Natural Language Interfaces for Procedural Content Generation in Games
- Author(s): Mobramaein Kano, Afshin
- Advisor(s): Whitehead, Jim
- et al.
Mixed-Initiative Procedural Content Generation (MI-PCG) focuses on developing systems that allow users with diverse technical backgrounds to co-create interesting and novel game content in collaboration with a computational agent. These systems provide a front-end for users to interact with a generator by means of placing different constraints, or modifying a variety of the generator's parameters. While these systems provide significantly enhanced design support over traditional design tools, there exists areas of opportunity to address shortcomings in these systems such as high user interface complexity (too many controls presented, little feedback provided) and the lack of a model of designer intent (the system can reason over constraints but does not understand the expressive intent of the user).
We believe that natural language interfaces can provide a way of addressing these areas by utilizing the expressiveness of natural language as an input for mixed-initiative systems in a way that it can reduce interface complexity by converting natural language queries into design space movements or constraints for the generator to act upon. By reducing all input to a single query the natural language interface can make the appropriate selection of parameters and controls that can result in the desired result for the user compared to the traditional modification of one control at a time in a traditional graphical user interface. Furthermore, the issue of designer intent can be addressed by creating a mapping of natural language concepts into a series of parameter combinations that allows for multi-dimensional movements in the design space of the generator, rather than manipulating a series of controls sequentially to achieve the same effect.
In this thesis we explore the design and implementations of natural languages in MI-PCG systems through the development of a design methodology for encoding natural language understanding into MI-PCG systems and the implementation of two proof of concept systems named CADI and WATER4-NL for different use case scenarios such as automated game design and shader manipulation respectively. Furthermore a user study based evaluation of WATER4-NL and its results are presented and discussed.