The aim of this project is to develop efficient algorithms, inspired by social interactions in living species in a swarm, for the control of a group of non-homogeneous vehicles to perform desired tasks. In particular, vehicles are not equipped with the same type of sensors or motion abilities. Challenges arising from these constraints will be tackled in this project. Methodologies based on the multi-agent concept have arisen as a promising paradigm for coordinating, controlling and modelling complex systems such as transportation, resource allocation and production planning. The success of cooperation interrelates and depends on the sharing and exchange of information among every agent within the group. This necessitates a multi-objective optimal solution where the use of intelligent computation techniques is attractive in terms of their effectiveness. To this end, the emerging agent-based algorithms can bring new dimensions to the cooperative control problem, as the biologically inspired capability of social interaction and self-experience prompts directly to dynamic strategies in dealing with complexity and optimality.