A Projection-Based Approach for Real-Time Assessment and Playability Check for Physics-Based Games

Abstract. This paper introduces an authoring tool for physics-based puzzle games that supports game designers through providing visual feedback about the space of interactions. The underlying algorithm accounts for the type and physical prop-erties of the different game components. An area of influence, which identifies the possible space of interaction, is identified for each component. The influence areas of all components in a given design are then merged considering the com-ponents ’ type and the context information. The tool can be used offline where complete designs are analyzed and the final interactive space is projected, and online where edits in the interactive space are projected on the canvas in realtime permitting continuous assistance for game designers and providing informative feedback about playability.

The experience-driven perspective

Ultimately, content is generated for the player. But so far, our algorithms have not taken specific players into account. Creating computational models of a player’s behaviour, preferences, or skills is called player modelling. With a model of the player, we can create algorithms that create content specifically tailored to that player. The experience-driven perspective on procedural content generation provides a framework for content generation based on player modelling; one of the most important ways of doing this is to use a player model in the evaluation function for search-based PCG. This chapter discusses different ways of collecting and encoding data about the player, primarily player experience, and ways of modelling this data. It also gives examples of different ways in which such models can be used.peer-reviewe

Evaluating content generators

Evaluating your content generator is a very important task, but difficult to do well. Creating a game content generator in general is much easier than creating a good game content generator—but what is a “good” content generator? That depends very much on what you are trying to create and why. This chapter discusses the importance and the challenges of evaluating content generators, and more generally understanding a generator’s strengths and weaknesses and suitability for your goals. In particular, we discuss two different approaches to evaluating content generators: visualizing the expressive range of generators, and using questionnaires to understand the impact of your generator on the player. These methods could broadly be called top-down and bottom-up methods for evaluating generators.peer-reviewe