Worker connectivity: a simulation model of variation in worker communication and its effects on task performance

We develop a simulation model of worker connectivity to analyze how variation in worker communication can influence task performance. The model generates predictions about how colony demography, worker communicative behavior, and worker cognition will affect the rate of recruitment of workers to a new task. The model explores some mechanisms for modulating the recruitment of workers. Under the conditions of our model-probabilistic interactions that lower worker's response thresholds to tasks-worker recruitment follows a logistic growth pattern. The rate of recruiting workers increases exponentially toward an inflection point when 50% of the available force has been activated, then decreases toward the upper asymptote (all workers recruited). Many relevant features of colony design and worker behavior, including group size, probability of interacting, and strength of interaction effects on receivers, show a positive but decelerating effect on the rate of worker recruitment. We also identify features of worker cognition that can influence task recruitment, focusing on the time course of worker's memories about previous interactions. Both learning (e.g., sensitization) and forgetting about previous interactions can influence the rate of worker recruitment to a task. The model suggests that worker cognition may be shaped by natural selection on task performance at the colony level. Forgetting about interactions may be especially costly, because it leads to unpredictable patterns of worker recruitment. We also show that social inhibition, when coupled with excitatory interactions, can effectively modulate worker recruitment at the colony level.