Simulating the Growth and Diffusion of Knowledge
in Agent Societies
Piotr Dollar, Paul Laskowski & Marshall Van Alstyne
mvanalst@umich.edu, mvanalst@umich.edu, mvanalst@umich.edu
The question of how to simultaneously promote growth
and diffusion of ideas exhibits difficult yet pressing tradeoffs. To
economists, it concerns the relationship between economic health and incentives
for sharing information. When does the stimulus to innovation, founded on
a profit motive, collide with access to information source material, which
exhibits properties of a public good? To the legal profession, it influences
what types of ideas should be intellectual property. Is society collectively
improved when rights to information are broader or narrower, longer or shorter?
To computer scientists, this tension is manifest as a debate in the production
of software. Is an open source or proprietary model superior?
To policy analysts, growth and diffusion are related to furnishing information
access. Are improved communications technologies enough to bring quality
information to those who seek it, and if not, why not?
To examine the tradeoffs, we have begun developing an
Information Growth and Diffusion (IGD) simulator (http://www.si.umich.edu/~mvanalst/iShare/).
It seeks to bridge a gap between software applications that model general
system dynamics and those that focus on low-level agent interactions.
It can track the entire flow of knowledge, and more general agent properties,
under a wide variety of agent behaviors. As information passes between
agents, the simulator can compute exactly how much information is shared
exclusively by each possible subset of agents in a society. We show that
the IGD simulator efficiently simulates, or "docks," a wide variety of agent-based
models. Thus, IGD applies broadly to the comparative study of models,
facilitating the exploration of relationships between models and revealing
what assumptions dictate model behavior.
Moreover, the IGD simulator permits deep exploration
of the relationship between local structure and global dynamics. At
the agent level, users can specify agent connections manually, or as a function
of the current system environment. These local connections determine
how the system behaves on the global level. Furthermore, dynamic agent-choice
strategies create a feedback mechanism that allows agents to alter their
individual behaviors as the global environment changes through time.
We designed the IGD simulator both to be a foundation
on which to study and compare particular models, and also a communications
tool, with resources for demonstrating the properties of different models
through interactive tutorials. Because users can alter model assumptions
without knowledge of a programming language, a wide audience may find the
simulator accessible. Students and educators can take advantage of
the tutorials to clarify and explore complex material. Researchers
can take advantage of the relative ease of implementing new models to quickly
test new theories. Under an open source framework, scholars interested
in economics, sociology, information technology, and other fields may wish
to contribute further improvements to the source code.