In some situations, MADM matrix is not distinguished completely at the first stage of decision making, because of the complexity of environment. These complexities lead to incomplete cognition and non-optimal decision making. In such ”semi-structured” environment, due to its high degree of complexity, the whole environment is not identifiable for Decision Maker (DM). We design an autonomous agent for semi-structured MADM that solves problems when alternatives have incomplete structure and DM is not able to recognize the whole alternatives of the environment for optimal decision making. The proposed model is a systematic approach for semi-structured MADM with multi-layer mathematical model. The Agent's Stepwise Response Generator (ASRG) moves in semi-structured environment over decision surface step by step to generate hidden alternatives. The new alternatives are designed to go through Feasibility Analyzer and Dynamic Filter Module. The procedure is continued with a closed loop feedback which results in the construction of the Meta-Decision phase.