A swarm can be described as a group of individuals using direct and indirect communication to act without central command with high efficiency in problem solving. For example, the insect society as a whole is extremely efficient due to a sophisticated form of self-organization is based on an indirect communication between its members. This communication is both between the members and their environment. For example the ant behaviour leads to repeatedly finding near optimum strategies in food supply, logistics and formicary construction. Studies of this behaviour have led to the first usable algorithms in the solution of logistical problems, in evolutionary programming and in manufacturing planning and control. A few examples will be presented. This paper will further study the differences between construction intelligence and swarm intelligence and discuss the possibilities to adapt this evolution to systems and problems of construction processes. First considerations have shown that the principles of the existing ant algorithms and simulation tools of manufacturing can be used in construction as well. In case of disturbances fast reorganization of processes can be developed using the algorithm. Modifications have to be made in terms of a number of definitions and system parameters. Any self-organizing system relies on frequent measurement, rapid distribution of information and near optimum reactions. By improving the related abilities construction can be made more transparent and goal-oriented. The paper is concluded with considerations as to whether swarm intelligence and derived algorithms can make a contribution to a construction theory (understanding the processes).
Swarm Intelligence, ant colony approach, wasp colony approach, managing the process, optimizing construction processes, resource planning