D³G²A is a new multi-agent approach which addresses additive constraint satisfaction problems (SigmaCSPs). This approach is inspired by the guided genetic algorithm (GGA) and by the dynamic distributed double guided genetic algorithm for Max_CSPs. It consists of agents dynamically created and cooperating in order to solve the problem. Each agent performs its own GA. First, our approach will be enhanced by a new parameter called guidance operator. The latter allows not only diversification but also an escaping from local optima. In the second step, the agents performed GAs will, no longer be the same. This is stirred by NEO-DARWINISM theory and the nature laws. In fact the new algorithm will let the species agents able to count their own GA parameters. In order to show D³G²A advantages, the approach and the GGA are applied on the radio link frequency allocation problem (RLFAP). The experimental comparison is provided