  The AI4GCC competition presents a bold step forward in the direction of
integrating machine learning with traditional economic policy analysis. Below,
we highlight two potential areas for improvement that could enhance the
competition's ability to identify and evaluate proposed negotiation protocols.
Firstly, we suggest the inclusion of an additional index that accounts for
consumption/utility as part of the evaluation criteria. Secondly, we recommend
further investigation into the learning dynamics of agents in the simulator and
the game theoretic properties of outcomes from proposed negotiation protocols.
We hope that these suggestions can be of use for future iterations of the
competition/simulation.
