<p>Water waves help aquatic animals locate environmental stimuli. While previous studies suggest that leech mechanoreceptors have evolved to respond to relevant wave frequencies, it remains unclear how information from multiple sensors is combined and processed. This work presents a simplified computational model that mimics leech goal seeking behavior in an agent-based simulation. A simulated leech (agent) was tasked with finding the source of an artificial water wave stimulus. The agent’s distributed mechanoreceptor array detected wave motion, which was processed with a computational neuroscience Winner-Take-All (WTA) framework to generate motion commands. The computational model’s performance aligned with data from animal experiments. The model also enables us to address questions about how different patterns of sensor ablation or placement might affect navigation performance in the animal. In this way, our model can complement animal experiments by enabling questions to be posed that are challenging to address with live animals. Furthermore, through considering how biological systems may process distributed information, our study may also provide insights into novel approaches for processing data from multiple sensors in man-made systems.</p>