TY - GEN
T1 - Topological analysis of numerosity-constrained social networks
AU - Abaid, Nicole
AU - Porfiri, Maurizio
PY - 2010
Y1 - 2010
N2 - In this study, we present a class of directed graphs with bounded degree sequences, which embodies the physical phenomenon of numerosity found in the collective behavior of large animal groups. Behavioral experiments show that an animal's perception of number is capped by a critical limit, above which an individual perceives a nonspecific "many". This species-dependent limit plays a pivotal role in the decision making process of large groups, such as fish schools and bird flocks. Here, we consider directed graphs whose edges model information-sharing between individual vertices. We incorporate the numerosity phenomenon as a critical limit on the intake of information by bounding the degree sequence and include the variability of cognitive processes by using a random variable in the network construction. We analytically compute measures of the expected structure of this class of graphs based on cycles, clustering, and sorting among vertices. Theoretical results are verified with numerical simulation.
AB - In this study, we present a class of directed graphs with bounded degree sequences, which embodies the physical phenomenon of numerosity found in the collective behavior of large animal groups. Behavioral experiments show that an animal's perception of number is capped by a critical limit, above which an individual perceives a nonspecific "many". This species-dependent limit plays a pivotal role in the decision making process of large groups, such as fish schools and bird flocks. Here, we consider directed graphs whose edges model information-sharing between individual vertices. We incorporate the numerosity phenomenon as a critical limit on the intake of information by bounding the degree sequence and include the variability of cognitive processes by using a random variable in the network construction. We analytically compute measures of the expected structure of this class of graphs based on cycles, clustering, and sorting among vertices. Theoretical results are verified with numerical simulation.
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U2 - 10.1115/DSCC2010-4099
DO - 10.1115/DSCC2010-4099
M3 - Conference contribution
AN - SCOPUS:79958220470
SN - 9780791844175
T3 - ASME 2010 Dynamic Systems and Control Conference, DSCC2010
SP - 931
EP - 937
BT - ASME 2010 Dynamic Systems and Control Conference, DSCC2010
T2 - ASME 2010 Dynamic Systems and Control Conference, DSCC2010
Y2 - 12 September 2010 through 15 September 2010
ER -