Dante & OpShed: 3D Simulation Tools for Physical Security
Abstract not provided.
Publications
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Jump to search filtersAnalyzing Effects of Public Communication onto Player Behavior in Massively Multiplayer Online Games
Abstract not provided.
A data driven approach to assess team performance through team communication
Abstract not provided.
Agent Based Modeling Social Phenomena and Massively Multiplayer Online Games
Massively Multiplayer Online Games as a source of data for empirical validation
Abstract not provided.
A Data-Driven Approach to Assessing Team Performance through Team Communication
Abstract not provided.
Large-Scale Conflicts in Massively Multiplayer Online Games
Abstract not provided.
Validating Agent Based Models Through Virtual Worlds
Abstract not provided.
Trainable automated forces
Abstract not provided.
Enabling immersive simulation
The object of the 'Enabling Immersive Simulation for Complex Systems Analysis and Training' LDRD has been to research, design, and engineer a capability to develop simulations which (1) provide a rich, immersive interface for participation by real humans (exploiting existing high-performance game-engine technology wherever possible), and (2) can leverage Sandia's substantial investment in high-fidelity physical and cognitive models implemented in the Umbra simulation framework. We report here on these efforts. First, we describe the integration of Sandia's Umbra modular simulation framework with the open-source Delta3D game engine. Next, we report on Umbra's integration with Sandia's Cognitive Foundry, specifically to provide for learning behaviors for 'virtual teammates' directly from observed human behavior. Finally, we describe the integration of Delta3D with the ABL behavior engine, and report on research into establishing the theoretical framework that will be required to make use of tools like ABL to scale up to increasingly rich and realistic virtual characters.
Preparing for the aftermath: Using emotional agents in game-based training for disaster response
2008 IEEE Symposium on Computational Intelligence and Games, CIG 2008
Ground Truth, a training game developed by Sandia National Laboratories in partnership with the University of Southern California GamePipe Lab, puts a player in the role of an Incident Commander working with teammate agents to respond to urban threats. These agents simulate certain emotions that a responder may feel during this high-stress situation. We construct psychology-plausible models compliant with the Sandia Human Embodiment and Representation Cognitive Architecture (SHERCA) that are run on the Sandia Cognitive Runtime Engine with Active Memory (SCREAM) software. SCREAM's computational representations for modeling human decision-making combine aspects of ANNs and fuzzy logic networks. This paper gives an overview of Ground Truth and discusses the adaptation of the SHERCA and SCREAM into the game. We include a semiformal descriptionof SCREAM. ©2008 IEEE.
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