Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Civilizations as networks: trade, war, diplomacy, and command-control
Complexity - Special issue: Selection, tinkering, and emergence in complex networks
Weaving a social fabric into existing software
Proceedings of the 4th international conference on Aspect-oriented software development
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Boosting cultural algorithms with a heterogeneous layered social fabric influence function
Computational & Mathematical Organization Theory
The emergence of cultural hierarchical social networks in complex environments
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
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Our previous work on real-valued function and Engineering Optimization problems had shown that cultural learning emerged as the result of a more focused meta-level interaction or swarming of knowledge sources, “Knowledge Swarms” in the belief space. These meta-level swarms induced the swarming of individuals in a formed social network in the population space, “Cultural Swarms”. The interaction of these knowledge sources with the population swarms produced emergent phases of problem solving. This reflected an algorithmic process that emerged from the interaction of the knowledge sources under the influence of a social fabric using different configurations. In this paper we investigate the extent to which these emergent phenomena are also visible within dynamic environments. We motivate the discussion in terms of a simulation model of a reversible switching surface visualized in our Cultural Algorithm Toolkit (CAT). We demonstrate how we can program such changes in surface structure using our new influence function that we integrate in our framework.