Over the last decade there has been a growing interest on Intelligent Agents and Multi-Agent Systems (MAS) in several fields such as Artificial Intelligence (AI), Software Engineering, Psychology, etc… Different problems can be solved in these fields by creating societies of agents that communicate with each other. Nevertheless, when the number of agents is large and the connectivity is extensive, the system suffers from overhead in the communication among agents due to the large number messages exchanged. This work addresses the search for an optimal communication topology to avoid these situations. This optimal topology is characterized by the use of a redirecting probability in the communication. The redirection of a communication is performed before the execution of the MAS. Once agents start the execution, the topology is fixed and remains unchanged. This characteristic is useful in those systems where a given topology can not be changed as, for example, in wired networks. On the other hand, in the proposed solution agents contain a local message discrimination process as a function of the sender of the message. Experiments show an important improvement in terms of a reduction in the number of iterations needed to solve the problem and also in the number of messages exchanged.