Evolutionary agents to model societies and organizations

People involved

This is a set of project ideas concerning agent-based computational models of individuals in evolving societies and organizations. These models fall within the general framework of Agent-based Computational Economics (for more information about this research area go to the excellent ACE site).

We are interested in studying the adaptive topologies and dynamics predicted by modeling the evolution of different kinds of social networks/interactions. For example, we expect certain evolved networks to display mixtures of regularity and randomness, as in small-world networks. Projects include:

Referral networks in labor markets (agents allocate resources to extend their friendship networks or to increase their qualifications, for maximizing their employment satisfaction)
Dynamics of rules in commons dilemmas (what causes individuals to invest in rule development, and which cognitive processes explain the ability of humans to craft new rules) -- supported by NSF HSD Grant
Analysing complexity of agent-based models (in particular for modeling land-owners' decision strategies and learning mechanisms, and how they affect historical patterns of land-cover change)
Management networks in organizations (innovative ideas pass through communication hierarchies filtered by noise, to be implemented by firms in a competitive environment)

Tei Laine won the best poster award at the WISP 7th Annual Research Day (see all the posters here).

Some papers are available here.

Source code for "Emerging Small-World Referral Networks in Evolutionary Labor Markets" in IEEE Trans. Evol. Comp. is available here.

This material is partly based upon work supported by the National Science Foundation under grant No. HSD-0432894. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.