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.
- 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
(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
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.