The significance of Leonid Brekhovskikh to the ocean acoustics is undisputed. He was pioneering not only in terms of fundamental understanding of the ocean acoustic waveguide, but also the development of efficient and numerically stable approaches to propagation of sound in a stratified ocean. As such he has been an inspiration to a whole generation of model developers, leading to today’s suite of extremely powerful wave theory models, capable of accurately representing the complexity of the shallow-water ocean waveguide physics. The availability of these computational tools have in turn led to major advances in adaptive, model-based signal-processing techniques. However, such computationally intensive approaches are not necessarily optimal for the next generation of acoustic sensing systems. Thus, ocean observation in general is currently experiencing a paradigm shift away from platform-centric sensing concepts toward distributed sensing systems, made possible by recent advances in underwater robotics. In addition to a fully autonomous capability, the latency and limited bandwidth of underwater communication make on-board processing essential for such systems to be operationally feasible. In addition, the reduced sensing capability of the smaller physical apertures may be compensated by using mobility and artificial intelligence to dynamically adapt the sonar configuration to the environment and the tactical situation, and by exploiting multiplatform collaborative sensing. The development of such integrated sensing and control concepts for detection, classification, and localization requires extensive use of artificial intelligence incorporating a fundamental understanding of the ocean acoustic waveguide. No other sources in literature provide this with the clarity and depth that is the trademark of Academician Brekovskikh’s articles and classical textbooks. [Work supported by ONR.]