  The Metaverse is regarded as the next-generation Internet paradigm that
allows humans to play, work, and socialize in an alternative virtual world with
immersive experience, for instance, via head-mounted display for Virtual
Reality (VR) rendering. With the help of ubiquitous wireless connections and
powerful edge computing technologies, VR users in wireless edge-empowered
Metaverse can immerse in the virtual through the access of VR services offered
by different providers. However, VR applications are computation- and
communication-intensive. The VR service providers (SPs) have to optimize the VR
service delivery efficiently and economically given their limited communication
and computation resources. An incentive mechanism can be thus applied as an
effective tool for managing VR services between providers and users. Therefore,
in this paper, we propose a learning-based Incentive Mechanism framework for VR
services in the Metaverse. First, we propose the quality of perception as the
metric for VR users immersing in the virtual world. Second, for quick trading
of VR services between VR users (i.e., buyers) and VR SPs (i.e., sellers), we
design a double Dutch auction mechanism to determine optimal pricing and
allocation rules in this market. Third, for auction communication reduction, we
design a deep reinforcement learning-based auctioneer to accelerate this
auction process. Experimental results demonstrate that the proposed framework
can achieve near-optimal social welfare while reducing at least half of the
auction information exchange cost than baseline methods.
