This paper analyzes the performance of three different semi-active control algorithms used to calculate and manage the optimal damping forces generated by a pair of magnetorheological (MR) dampers installed in a two-story building. The semi-active algorithms used are the linear quadratic regulator (LQR) associated with the clipped optimal algorithm, an algorithm based on a prediction model and a dynamic inverse model using nonlinear autoregressive exogenous (NARX)-type artificial neural networks, and a decision-making algorithm based on fuzzy logic. Additionally, the performances of the proposed semi-active algorithms are compared to those of passively used control devices. The results show response value reductions exceeding 50% for all the semi-active control strategies, which considerably outperformed the passive control. The three control strategies are thus confirmed as interesting tools with potential applications as MR damper administrators.