The proposed optimal bidding strategy, MIA-RVelous, can be extended to handle more complex negotiation scenarios by incorporating multi-issue considerations and dynamic acceptance models. In multi-issue negotiations, where multiple aspects are negotiated simultaneously, the agent can adapt the bidding strategy to account for the interdependencies between different issues. This extension would involve optimizing the bid sequence not only based on individual issue utilities but also considering the overall utility of the package deal.
For negotiations with dynamic acceptance models, where the opponent's acceptance probabilities change over time or based on certain events, the bidding strategy can be enhanced to incorporate adaptive learning mechanisms. By continuously updating the opponent model and adjusting the bidding strategy in real-time, the agent can react to changing acceptance probabilities effectively. This adaptation can be achieved through reinforcement learning techniques or Bayesian updating of the opponent model.
In essence, extending the optimal bidding strategy to handle more complex negotiation scenarios involves incorporating additional decision variables, adapting to changing environments, and considering the holistic utility of multi-issue negotiations.