TY - GEN
T1 - Quantization games on networks
AU - Mani, Ankur
AU - Varshney, Lav R.
AU - Pentland, Alex
PY - 2013/8/8
Y1 - 2013/8/8
N2 - We consider a network quantizer design setting where agents must balance fidelity in representing their local source distributions against their ability to successfully communicate with other connected agents. By casting the problem as a network game, we show existence of Nash equilibrium quantizer designs. For any agent, under Nash equilibrium, the word representing a given partition region is the conditional expectation of the mixture of local and social source probability distributions within the region. Further, the network may converge to equilibrium through a distributed version of the Lloyd-Max algorithm. In contrast to traditional results in the evolution of language, we find several vocabularies may coexist in the Nash equilibrium, with each individual having exactly one of these vocabularies. The overlap between vocabularies is high for individuals that communicate frequently and have similar local sources. Finally, we argue error in translation along a chain of communication does not grow if and only if the chain consists of agents with shared vocabulary.
AB - We consider a network quantizer design setting where agents must balance fidelity in representing their local source distributions against their ability to successfully communicate with other connected agents. By casting the problem as a network game, we show existence of Nash equilibrium quantizer designs. For any agent, under Nash equilibrium, the word representing a given partition region is the conditional expectation of the mixture of local and social source probability distributions within the region. Further, the network may converge to equilibrium through a distributed version of the Lloyd-Max algorithm. In contrast to traditional results in the evolution of language, we find several vocabularies may coexist in the Nash equilibrium, with each individual having exactly one of these vocabularies. The overlap between vocabularies is high for individuals that communicate frequently and have similar local sources. Finally, we argue error in translation along a chain of communication does not grow if and only if the chain consists of agents with shared vocabulary.
UR - http://www.scopus.com/inward/record.url?scp=84881034119&partnerID=8YFLogxK
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U2 - 10.1109/DCC.2013.37
DO - 10.1109/DCC.2013.37
M3 - Conference contribution
AN - SCOPUS:84881034119
SN - 9780769549651
T3 - Data Compression Conference Proceedings
SP - 291
EP - 300
BT - Proceedings - DCC 2013
T2 - 2013 Data Compression Conference, DCC 2013
Y2 - 20 March 2013 through 22 March 2013
ER -