We present computer simulations and analysis for the global behavior arising from a population of heterogeneous social agents acting with bounded rationality. The particular model studied, termed the “bar-attendance” model, offers a simple paradigm for such complex adaptive systems involving competitive agents. The model considers p adaptive agents, each possessing n predic tion rules chosen randomly from a pool of N, who attempt to attend a bar where the seating capacity is s. The global attendance time-series x(t) has a mean near, but not equal to, s. Surprisingly, the standard deviation or “volatility” of x(t) can show a minimum with increasing adaptability of the individual agents. Various arguments based on random walk models are dis cussed. It is shown that effects of crowding have to be included in order to understand the volatil ity in this system.
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Behavioral Neuroscience