Visualisation of semantic architectural information within a game engine environment

Because of the importance of graphics and information within the domain of architecture, engineering and construction (AEC), an appropriate combination of visualisation technology and information management technology is of utter importance in the development of appropriately supporting design and construction applications. We therefore started an investigation of two of the newest developments in these domains, namely game engine technology and semantic web technology. This paper documents part of this research, containing a review and comparison of the most prominent game engines and documenting our architectural semantic web. A short test-case illustrates how both can be combined to enhance information visualisation for architectural design and construction

Situating Cognition within the Virtual World

Cognitive architectures and virtual environments have a long history of use within the cognitive science community. Few studies, however, have sought to combine the use of these technologies to support computational studies into embodied, extended, situated and distributed (EESD) cognition. Here, we explore the extent to which the ACT-R cognitive architecture and the Unity game engine can be used for these purposes. A range of issues are discussed including the respective responsibilities that the cognitive architecture and game engine have for the implementation of specific processes, the extent to which the representational and computational capabilities of cognitive architectures are suited to the modeling of EESD cognitive systems, and the extent to which the kind of embodiment seen in the case of so-called ‘embodied virtual agents’ resembles that seen in the case of real-world bio-cognitive systems. These issues are likely to inform the focus of future research efforts concerning the integrative use of virtual environments and cognitive architectures for the computational modeling and simulation of EESD cognitive processes

Situating Cognition within the Virtual World

Cognitive architectures and virtual environments have a long history of use within the cognitive science community. Few studies, however, have sought to combine the use of these technologies to support computational studies into embodied, extended, situated and distributed (EESD) cognition. Here, we explore the extent to which the ACT-R cognitive architecture and the Unity game engine can be used for these purposes. A range of issues are discussed including the respective responsibilities that the cognitive architecture and game engine have for the implementation of specific processes, the extent to which the representational and computational capabilities of cognitive architectures are suited to the modeling of EESD cognitive systems, and the extent to which the kind of embodiment seen in the case of so-called ‘embodied virtual agents’ resembles that seen in the case of real-world bio-cognitive systems. These issues are likely to inform the focus of future research efforts concerning the integrative use of virtual environments and cognitive architectures for the computational modeling and simulation of EESD cognitive processes

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Using a Cognitive Architecture for Opponent Target Prediction

One of the most important aspects of a compelling game AI is that it anticipates the player’s actions and responds to them in a convincing manner. The first step towards doing this is to understand what the player is doing and predict their possible future actions. In this paper we show an approach where the AI system focusses on testing hypotheses made about the player’s actions using an implementation of a cognitive architecture inspired by the simulation theory of mind. The application used in this paper is to predict the target that the player is heading towards, in an RTS-style game. We improve the prediction accuracy and reduce the number of hypotheses needed by using path planning and path clustering