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Social Learning and Social Capital: Socioeconomic Simulations Using Mathematica
Richard J. Gaylord
University of Illinois at Urbana-Champaign
Computer simulation provides a powerful theoretical tool for studying human social
behavior. In this talk, we'll look at simulation models of social phenomena, using a
bottom-up or agent-based approach. This approach differs from traditional socioeconomic
modeling in that it assumes that: 1) people are heterogeneous, each having his or her own
identity, traits, tastes, and memories; 2) people can think rationally or irrationally,
intelligently, or naively; 3) people can directly interact unilaterally or multilaterally
without the intervention of a central authority; 4) people can change their behavior as
they learn from experience and adapt; and 5) people are mobile and can move around
simultaneously or ansynchronously.
We'll develop and discuss simulation models of a variety of social phenomena, including the following.
- Social Learning
- Social Capital
- Nonlocal Phenomena
Richard J. Gaylord is a Professor in the Department of Materials Science and
Engineering at the University of Illinois at Urbana-Champaign. He published over 50
technical articles in the field of theoretical materials physics before going into the
field of computer simulations. He has authored Simulating Society: A Mathematica Toolkit
for Modeling Socioeconomic Behavior, MODELING NATURE: Cellular Automata Simulations Using
Mathematica, Computer Simulations with Mathematica: Explorations in Complex Physical and
Biological Systems, and Introduction to Programming with Mathematica
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