SOAR: an architecture for general intelligence
Artificial Intelligence
TREAT: a new and efficient match algorithm for AI production systems
TREAT: a new and efficient match algorithm for AI production systems
Production matching for large learning systems
Production matching for large learning systems
System for authoring highly interactive, personality-rich interactive characters
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
TREE: the heuristic driven join strategy of a RETE-like matcher
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Proceedings of the 2012 Symposium on Military Modeling and Simulation
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The behavior models that control simulated warfighters in most modeling and simulation (M&S) efforts are fairly simple, relying predominantly on behavior scripting and simple rules to produce actions. As a result, the simulated entities do not reflect critical situational awareness factors used by Ground Soldiers or allow for the modeling of devices that influence situational awareness, such as user defined operating pictures (UDOPs). This paper describes our approach to this challenge, providing 1) a rule-based method for modeling Ground Soldier situational awareness and devices that influence situational awareness and 2) a user friendly graphical authoring tool for creating these rules. We present a requirements analysis of this modeling task and discuss and provide examples of how our method may be employed for modeling Soldier perception and inferences as well as devices that affect situational awareness.