Title
Noisy preferential attachment and language evolution
Abstract
We study the role of the agent interaction topology in distributed language learning In particular, we utilize the replicator- mutator framework of language evolution for the creation of an emergent agent interaction topology that leads to quick convergence In our system, it is the links between agents that are treated as the units of selection and replication, rather than the languages themselves We use the Noisy Preferential Attachment algorithm, which is a special case of the replicator-mutator process, for generating the topology The advantage of the NPA algorithm is that, in the short-term, it produces a scale-free interaction network, which is helpful for rapid exploration of the space of languages present in the population A change of parameter settings then ensures convergence because it guarantees the emergence of a single dominant node which is chosen as teacher almost always.
Year
DOI
Venue
2006
10.1007/11840541_63
SAB
Keywords
Field
DocType
mutator framework,agent interaction topology,noisy preferential attachment,scale-free interaction network,parameter setting,noisy preferential attachment algorithm,npa algorithm,rapid exploration,quick convergence,language evolution,emergent agent interaction topology,scale free,language learning,interaction network
Convergence (routing),Information system,Population,Computer science,Interaction network,Language acquisition,Artificial intelligence,Almost surely,Preferential attachment,Special case
Conference
Volume
ISSN
ISBN
4095
0302-9743
3-540-38608-4
Citations 
PageRank 
References 
1
0.35
4
Authors
2
Name
Order
Citations
PageRank
Samarth Swarup121328.37
Les Gasser21601261.00