Human behavior models for agents in simulators and games: part I: enabling science with PMFserv
Presence: Teleoperators and Virtual Environments
Human behavior models for agents in simulators and games: part II: gamebot engineering with PMFserv
Presence: Teleoperators and Virtual Environments
Modeling factions for "effects based operations": part I--leaders and followers
Computational & Mathematical Organization Theory
Modeling factions for `effects based operations', part II: behavioral game theory
Computational & Mathematical Organization Theory
Web-based multi-agent system architecture in a dynamic environment
International Journal of Knowledge-based and Intelligent Engineering Systems
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Many simulators today contain traditional opponents and lack an asymmetric insurgent style adversary. InsurgiSim prototypes an embeddable testbed containing a threat network of agents that one can easily configure and deploy for training and analysis purposes. The insurgent network was constructed inside a socio-cognitive agent framework (FactionSim-PMFserv) that includes: (a) a synthesis of best-of-breed models of personality, culture, values, emotions, stress, social relations, mobilization, as well as (b) an IDE for authoring and managing reusable archetypes and their task-sets (Section 2). Agents and markups in this library are not scripted, and act to follow their values and fulfill their needs. So it's desirable to profile the agents (eg, faction leaders, cell logisticians, followers, bomb maker, financier, recruiter, etc.) as faithfully to the real world as possible. Doing this will improve the utility of InsurgiSim for studying what may be driving the insurgent agents in a given area of operation as Section 3 explains. InsurgiSim's bridge is an HLA federate and can be embedded to drive all or some of the insurgent agents in a 3rd party simulator. Three such examples are summarized in Section 4. The paper closes with next steps to improve InsurgiSim's capabilities and utility.