  In the context of IoT deployments, a multitude of devices concurrently
require network access to transmit data over a shared communication channel.
Employing symmetric strategies can effectively facilitate the collaborative use
of the communication medium among these devices. By adopting such strategies,
devices collectively optimize their transmission parameters, resulting in
minimized collisions and enhanced overall network throughput.
  Our primary focus centers on the formulation of symmetric (i.e., identical)
strategies for the sensors, aiming to optimize a finite horizon team objective.
The imposition of symmetric strategies introduces novel facets and complexities
into the team problem. To address this, we embrace the common information
approach and adapt it to accommodate the use of symmetric strategies. This
adaptation yields a dynamic programming framework grounded in common
information, wherein each step entails the minimization of a single function
mapping from an agent's private information space to the space of probability
distributions over possible actions.
  Our proposed policy/method incurs a reduced cumulative cost compared to other
methods employing symmetric strategies, a point substantiated by our simulation
results.
