We present a knowledge-based distribution concept for search problems that offer no natural way to determine several agents to cooperate in finding a solution. Systems based on our teamwork method use four types of agents: Experts and specialists use heuristics to generate results that are possible parts of solutions, referees judge the experts and their results determining the most promising ones and a supervisor collects these promising results to generate new problem descriptions that converge to a solution of the initial problem. The main difficulty of distributed systems, the communication overhead, is dealt with by restricting the work of referees and the supervisor to short so-called team meetings that interrupt the work of experts and specialists. The competition and cooperation of experts and specialists in this framework allow for synergetic effects that generate better and faster solutions to the search problems. We demonstrate these effects for instantiations of two very different kinds of search problems, automated theorem proving and optimization problems.