BUILDING HIGH FIDELITY HUMAN BEHAVIOR MODELS IN THE SIGMA COGNITIVE ARCHITECTURE (bibtex)
by Ustun, Volkan, Rosenbloom, Paul S., Kim, Julia and Li, Lingshan
Abstract:
Many agent simulations involve computational models of intelligent human behavior. In a variety of cases, these behavior models should be high-fidelity to provide the required realism and credibility. Cognitive architectures may assist the generation of such high-fidelity models as they specify the fixed structure underlying an intelligent cognitive system that does not change over time and across domains. Existing symbolic architectures, such as Soar and ACT-R, have been used in this way, but here the focus is on a new architecture, Sigma (!), that leverages probabilistic graphical models towards a uniform grand unification of not only the traditional cognitive capabilities but also key non-cognitive aspects, and which thus yields unique opportunities for construction of new kinds of non-modular high-fidelity behavior models. Here, we briefly introduce Sigma along with two disparate proof-of-concept virtual humans – one conversational and the other a pair of ambulatory agents – that demonstrate its diverse capabilities.
Reference:
BUILDING HIGH FIDELITY HUMAN BEHAVIOR MODELS IN THE SIGMA COGNITIVE ARCHITECTURE (Ustun, Volkan, Rosenbloom, Paul S., Kim, Julia and Li, Lingshan), In Proceedings of the 2015 Winter Simulation Conference, IEEE, 2015.
Bibtex Entry:
@inproceedings{ustun_building_2015,
	address = {Huntington Beach, CA},
	title = {{BUILDING} {HIGH} {FIDELITY} {HUMAN} {BEHAVIOR} {MODELS} {IN} {THE} {SIGMA} {COGNITIVE} {ARCHITECTURE}},
	isbn = {978-1-4673-9741-4},
	url = {http://dl.acm.org/citation.cfm?id=2888619.2888999},
	abstract = {Many agent simulations involve computational models of intelligent human behavior. In a variety of cases, these behavior models should be high-fidelity to provide the required realism and credibility. Cognitive architectures may assist the generation of such high-fidelity models as they specify the fixed structure underlying an intelligent cognitive system that does not change over time and across domains. Existing symbolic architectures, such as Soar and ACT-R, have been used in this way, but here the focus is on a new architecture, Sigma (!), that leverages probabilistic graphical models towards a uniform grand unification of not only the traditional cognitive capabilities but also key non-cognitive aspects, and which thus yields unique opportunities for construction of new kinds of non-modular high-fidelity behavior models. Here, we briefly introduce Sigma along with two disparate proof-of-concept virtual humans – one conversational and the other a pair of ambulatory agents – that demonstrate its diverse capabilities.},
	booktitle = {Proceedings of the 2015 {Winter} {Simulation} {Conference}},
	publisher = {IEEE},
	author = {Ustun, Volkan and Rosenbloom, Paul S. and Kim, Julia and Li, Lingshan},
	month = dec,
	year = {2015},
	keywords = {CogArch, Virtual Humans},
	pages = {3124--3125}
}
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