Current game worlds often fall short in providing consistency between the visual representation of the world and the way it feels, behaves, and reacts. This problem partly originates from the goaloriented and cost-effective nature of the game development process, which mostly favors ad hoc solutions for one particular game, rather than investing in concepts like reusability and emergent gameplay. In broader terms, we observe that game worlds miss semantics, and we argue that its deployment has the potential to bring about the consistency missing in their content. Therefore, we present a novel approach aimed at enriching virtual entities in game worlds with information about their roles, how they relate to others, and how they can affect and interact with players, NPCs, and with each other. We discuss several requirements to achieve these goals, and introduce a semantic model to represent game worlds. In order to support and validate this model, we have developed Entika, a framework to facilitate the deployment of semantics during game development, as well as its maintenance during run-time. Furthermore, we briefly discuss several applications that demonstrate the power of this semantic model for game worlds. After careful evaluation of our semantic game world model and framework, we conclude that a semantically rich world representation can substantially assist designers in creating much more consistent game worlds.@en

Recent advances in crowd simulation techniques have led to realistic agent and group behavior through elaborate behavioral models, complex motion planning algorithms and impressive physics systems. As many crowd simulation solutions typically target only specific types of environment and scenario, a variety of special-purpose methods and systems has emerged that are hard to re-configure and re-use in other contexts. Solving this situation demands a higher-level approach that takes re-use and configuration of crowds as a priority, for adequate application in a broad variety of scenarios, virtual environments and inter- action with the entities present in that environment. In this article we propose semantic crowds, a novel approach that allows one to re-use the same crowds for virtually any environment, and have them use the objects available in it in a meaningful manner, without any modification. To have the agents autonomously interact within any virtual world, we minimize in them the information relative to what objects do and how to use them. Instead, that information is stored in the objects themselves, which the agents can then query, based on what they plausibly want to achieve. To facilitate creating such crowds, we devel- oped an interactive crowd editor that provides high-level editing parameters for defining crowd templates. We illustrate the flexibility of semantic crowds by means of two cases, in which we let the same crowd populate quite differently configured airport terminal environments. These examples also highlight that this modular approach easily combines with your custom implementations of agent behavior model and/or motion planner.@en