The dial-A-ride problem consists of designing vehicle routes in the area of passenger transportation. Assuming that each vehicle can act autonomously, the problem can be modeled as a multi-Agent system. In that context, it is a complex decision process for each agent to determine what action to perform next. In this work, the agent function is evolved using genetic programming by synthesizing basic bits of information. Specialized dispatching rules are synthesized automatically that are adapted to the problem environment. We compare the evolved rules with other dispatching strategies for dynamic dial-A-ride problems on a set of generated benchmark instances. Additionally, since genetic programming is a whitebox-based approach, insights can be gained about important system parameters. For that purpose, we perform a variable frequency analysis during the evolutionary process.