  As humans, we hear sound every second of our life. The sound we hear is often
affected by the acoustics of the environment surrounding us. For example, a
spacious hall leads to more reverberation. Room Impulse Responses (RIR) are
commonly used to characterize environment acoustics as a function of the scene
geometry, materials, and source/receiver locations. Traditionally, RIRs are
measured by setting up a loudspeaker and microphone in the environment for all
source/receiver locations, which is time-consuming and inefficient. We propose
to let two robots measure the environment's acoustics by actively moving and
emitting/receiving sweep signals. We also devise a collaborative multi-agent
policy where these two robots are trained to explore the environment's
acoustics while being rewarded for wide exploration and accurate prediction. We
show that the robots learn to collaborate and move to explore environment
acoustics while minimizing the prediction error. To the best of our knowledge,
we present the very first problem formulation and solution to the task of
collaborative environment acoustics measurements with multiple agents.
