GEAMAS is a knowledge engineering environment for multi-agent simulation of complex systems. The basic architecture of GEAMAS is designed around three dimensions: MultiAgent Systems (MAS) software design, MAS knowledge abstraction and MAS services dimension. Each one of this third aspects, is implemented into several modular open software layers.First, the paper argues the benefits of a such architecture for a MAS environment. We especially present 1) how the MAS software design dimension enables to define appropriate tools levels for designing multi-agent systems 2) how MAS knowledge abstraction adds significant value to implement a computational model of agents 3) how MAS services dimension allows to correctly extend the GEAMAS environment by integrating new multi-agent concepts such as organization capacities or learning mechanisms.