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
Agent based human behavior modeling: a knowledge engineering based systems methodology for integrating social science frameworks for modeling agents with cognition, personality and culture
Assessing the complexity of plan recognition
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Human terrain data: what should we do with it?
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
An embeddable testbed for insurgent and terrorist agent theories: InsurgiSim
Intelligent Decision Technologies
Coordination, Organizations, Institutions and Norms in Agent Systems IV
Intelligent Decision Technologies - Engineering and management of IDTs for knowledge management systems
Rich socio-cognitive agents for immersive training environments: case of NonKin Village
Autonomous Agents and Multi-Agent Systems
Modeling effect of leaders in ethno-religious conflicts
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
Validating agent based social systems models
Proceedings of the Winter Simulation Conference
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This paper presents a synthetic approach for generating role playing simulation games intended to support analysts (and trainees) interested in testing alternative competing courses of action (operations) and discovering what effects they are likely to precipitate in potential ethno-political conflict situations. Simulated leaders and followers capable of playing these games are implemented in a cognitive modeling framework, called PMFserv, which covers value systems, personality and cultural factors, emotions, relationships, perception, stress/coping style and decision making. Of direct interest, as Sect. 1.1 explains, is mathematical representation and synthesis of best-of-breed behavioral science models within this framework to reduce dimensionality and to improve the realism and internal validity of the agent implementations. Sections 2 and 3 present this for leader profiling instruments and group membership decision-making, respectively. Section 4 serves as an existence proof that the framework has generated several training and analysis tools, and Sect. 5 concludes with lessons learned. Part II turns to the question of assessment of the synthesis and its usage in course of action studies.