Gaming and Simulating Ethno-Political Conflicts

This chapter begins by describing a universally recurring socio-cultural “game” of inter-group competition for control of resources. It next describes efforts to author software agents able to play the game as real humans would - which suggests the ability to study alternative ways to influence them, observe PMESII effects, and potentially understand how best to alter the outcomes of potential conflict situations. These agents are unscripted, but use their decision making to react to events as they unfold and to plan out responses. For each agent, a software called PMFserv operates its perception and runs its physiology and personality/value system to determine fatigue and hunger, injuries and related stressors, grievances, tension buildup, impact of rumors and speech acts, emotions, and various collective and individual action decisions. The chapter wraps up with a correspondence test from a SE Asian ethnic conflict, the results of which indicate significant correlation between real and agentbased outcomes.

[1]  William B. Gudykunst,et al.  Culture’s Consequences: Comparing Values, Behaviors, Institutions, and Organizations Across Nations [2nd edition]: Geert Hofstede , 2005 .

[2]  Richard W. Pew,et al.  Modeling human and organizational behavior : application to military simulations , 1998 .

[3]  J. Kennedy,et al.  Culture , Leadership , and Organizations : The GLOBE Study of 62 Societies , 2022 .

[4]  Roy J. Eidelson,et al.  Psychological Bases of Extreme Policy Preferences , 2007 .

[5]  Scott de Marchi.  Computational and Mathematical Modeling in the Social Sciences , 2005 .

[6]  Kevin O'Brien,et al.  Human Behavior Models for Agents in Simulators and Games: Part I: Enabling Science with PMFserv , 2006, Presence: Teleoperators & Virtual Environments.

[7]  Andrew Ortony,et al.  The Cognitive Structure of Emotions , 1988 .

[8]  B. Silverman,et al.  Human Behavior Models for Game-Theoretic Agents: Case of Crowd Tipping , 2002 .

[9]  M. Hermann.  ASSESSING LEADERSHIP STYLE: A TRAIT ANALYSIS , 2002 .

[10]  B. Silverman,et al.  How Emotions and Personality Effect the Utility of Alternative Decisions: A Terrorist Target Selection Case Study , 2001 .

[11]  E. Wood.  Modeling Robust Settlements to Civil War: Indivisible Stakes and Distributional Compromises , 2006 .

[12]  Richards J. Heuer,et al.  Psychology of Intelligence Analysis , 1999 .

[13]  Evelyn Williams,et al.  Human Performance Simulation. , 1977 .

[14]  Kesten C. Green,et al.  Forecasting Decisions in Conflict Situations: A Comparison of Game Theory, Role-playing, and Unaided Judgement , 2002 .

[15]  Gnana K. Bharathy,et al.  Agent based human behavior modeling: a knowledge engineering based systems methodology for integrating social science frameworks for modeling agents with cognition, personality and culture , 2006 .

[16]  Wolf Thom.  Culture, Leadership, and Organizations: The GLOBE Study of 62 Societies [review] / House, R. J., Hanges, P.J., & Javidan, M., Eds. , 2006 .

[17]  Sean A. Spence,et al.  Descartes' Error: Emotion, Reason and the Human Brain , 1995 .

[18]  N. Stanietsky,et al.  The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity , 2009, Proceedings of the National Academy of Sciences.

[19]  Gnana Bharathy,et al.  Sociocultural Games for Training and Analysis , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[20]  Barry G. Silverman,et al.  Constructing Virtual Asymmetric Opponents from Data and Models in the Literature: Case of Crowd Rioting , 2002 .

[21]  Albert O. Hirschman,et al.  Exit, Voice, and Loyalty , 1970 .

[22]  Joshua M Epstein,et al.  Modeling civil violence: An agent-based computational approach , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Gnana Bharathy,et al.  Human Behavior Models for Agents in Simulators and Games: Part II: Gamebot Engineering with PMFserv , 2006, Presence: Teleoperators & Virtual Environments.