Peter Heck, Dept. of
Comp. Science & Eng., Arizona State University, Tempe, AZ, USA
pheck@asu.edu
S. Ghosh, Dept. of
Comp. Science & Eng., Arizona State University, Tempe, AZ, USA
sumit.ghosh@asu.edu
Current literature in ant colony behavior includes efforts to study the
dynamic movement of ants through computer modeling, generating synthetic
ant trails through simple rules of behavior, modeling the influence of
genetic selection in the evolutionary behavior in ants, investigating the
division of labor in ant colonies, and examining the potential trapping of
ants in pheromone-induced trails, when the available food sources maintain
unlimited supplies. This paper focuses on understanding, objectively, the
emergence of the meta-level behavior of an ant colony as a function of the
rules that govern the behavior of the individual ants, the interactions
between them, and other environmental factors. A computer model of a
synthetic ant colony is developed that permits the precise description of
the unique behavior of each individual synthetic ant and its interactions
with other ants. Under individual ant behaviors, this paper studies
different search algorithms that are utilized uniformly by all ants, during
foraging. In addition, this paper introduces the notion of creativity,
wherein a few select ants adopt a very different search algorithm for
foraging and expend greater resources in an effort to locate more food
sources, where available. With respect to the key environmental factors,
this paper analyzes the influence of food sources with finite supplies and
the duration of the pheromone, before it vaporizes, on the foraging
behavior of ants. The performance metrics, obtained through simulation,
reflect the meta-level, emergent behavior, and include the simulation time
within which all available food sources are located, the rate of
identification of the food sources as a function of simulation time, and
the energy expended by the ants in the course of foraging. Performance
results reveal the presence of an optimal value for the duration of the
pheromone that yields the fastest foraging behavior for a given search
algorithm and a given number of ants within a fixed geography. Results also
reveal that, for all search strategies, while the presence of creative ants
may enhance the efficiency of foraging under long lasting pheromone trails,
the advantage is reversed for trails with optimal pheromone duration.