  Software architectures for conversational robots typically consist of
multiple modules, each designed for a particular processing task or
functionality. Some of these modules are developed for the purpose of making
decisions about the next action that the robot ought to perform in the current
context. Those actions may relate to physical movements, such as driving
forward or grasping an object, but may also correspond to communicative acts,
such as asking a question to the human user. In this position paper, we reflect
on the organization of those decision modules in human-robot interaction
platforms. We discuss the relative benefits and limitations of modular vs.
end-to-end architectures, and argue that, despite the increasing popularity of
end-to-end approaches, modular architectures remain preferable when developing
conversational robots designed to execute complex tasks in collaboration with
human users. We also show that most practical HRI architectures tend to be
either robot-centric or dialogue-centric, depending on where developers wish to
place the ``command center'' of their system. While those design choices may be
justified in some application domains, they also limit the robot's ability to
flexibly interleave physical movements and conversational behaviours. We
contend that architectures placing ``action managers'' and ``interaction
managers'' on an equal footing may provide the best path forward for future
human-robot interaction systems.
