Selective attention informs decision-making by biasing perceptual processing towards task-relevant stimuli. In experimental and computational literature, this is most often implemented through top-down excitation of selected stimuli. However, physiological and anatomical evidence shows that in certain situations, top-down signals could instead be inhibitory. In this study, we investigated how such an inhibitory mechanism of top-down attention compares with an excitatory one. We did so in a neurorobotics context where the agent was controlled using an established hierarchical architecture. We augmented the architecture with an attentional system that implemented top-down attention biasing as connection gains. We tested four models of top-down attention on the simulated agent performing a foraging task: without top-down biasing, with only excitatory top-down gain, with only inhibitory top-down gain, and with both excitatory and inhibitory top-down gain. We manipulated the reward-distractor ratio that was presented and assessed the agent's performance using accumulated rewards and the latency of the selection. Using these measures, we provide evidence that excitatory and inhibitory mechanisms of attention complement each other.