An Approach to Advance Higher Order Cross-cultural Awareness in Dismounted Soldiers

Abstract Cultural awareness is important for a range of operations from disaster assistance to active conflict. This paper illustrates the application of an acknowledged system of systems (SoS) to train dismounted soldiers in cultural awareness. Such training system is required to not only increase intelligence gathering opportunities but also minimize troop member loss during missions. Moreover, given the increase in the cultural interaction of dismounted soldiers, specific training is needed to raise cultural awareness. In this research an acknowledged (SoS) model of augmented cultural awareness centered on both agent-based simulation and body sensor networks is proposed. The immersive vest developed at Missouri University of Science and Technology helps assess the distributive intelligence (situational awareness) of both the dismounted soldier and civilians alike. This processed data is then used to train a similar prototype of the physical system environment as an agent based simulation. Strategies in agent's behavior are also described. This description allows him/her to adapt specific behaviors in response to the foreign civilian.

[1]  Fritz Drasgow,et al.  Training, Developing, and Assessing Cross-Cultural Competence in Military Personnel , 2011 .

[2]  Jeffrey M. Hausdorff,et al.  Fractal dynamics in physiology: Alterations with disease and aging , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Gary Klein,et al.  Sources of Power: How People Make Decisions , 2017 .

[4]  Cihan H. Dagli,et al.  Augmented Cognition in Human-System Interaction through Coupled Action of Body Sensor Network and Agent Based Modeling , 2013, CSER.

[5]  Ya'akov Gal,et al.  Training with automated agents improves people's behavior in negotiation and coordination tasks , 2014, Decis. Support Syst..

[6]  W. McEneaney,et al.  Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind , 2006 .

[7]  Harry Timmermans,et al.  Using Bayesian decision networks for knowledge representation under conditions of uncertainty in multi-agent land use simulation models , 2004 .

[8]  Anand S. Rao,et al.  BDI Agents: From Theory to Practice , 1995, ICMAS.

[9]  Sabarish V. Babu,et al.  Can Immersive Virtual Humans Teach Social Conversational Protocols? , 2007, 2007 IEEE Virtual Reality Conference.

[10]  Christine L. Lisetti,et al.  Emotion recognition from physiological signals using wireless sensors for presence technologies , 2004, Cognition, Technology & Work.

[11]  Richard L. Griffith,et al.  Theoretical and Practical Advances in the Assessment of Cross-Cultural Competence , 2012 .

[12]  C. H. Dagli,et al.  Development of an immersive training vest , 2012, 2012 IEEE Systems and Information Engineering Design Symposium.

[13]  Russell Beale,et al.  Affect and Emotion in Human-Computer Interaction, From Theory to Applications , 2008, Affect and Emotion in Human-Computer Interaction.

[14]  Allison Abbe,et al.  Cross-Cultural Competence in Army Leaders: A Conceptual and Empirical Foundation , 2007 .

[15]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[16]  Hugo Fuks,et al.  Wearable Computing: Accelerometers' Data Classification of Body Postures and Movements , 2012, SBIA.

[17]  Winston R. Sieck,et al.  A Cultural Belief Network Simulator , 2011, SBP.

[18]  K. Ross,et al.  Assessing the Development of Cross-Cultural Competence in Soldiers , 2010 .

[19]  J.S. Dahmann,et al.  Understanding the Current State of US Defense Systems of Systems and the Implications for Systems Engineering , 2008, 2008 2nd Annual IEEE Systems Conference.

[20]  Kunihiko Kaneko,et al.  Coupled maps with local and global interactions. , 2000, Chaos.