Cascaded consensus splitting for multi-branch contingency games

2026-09-29

AI Summary

This study addresses the lack of modeling for asynchronous intention revelation and the high computational cost of joint solving in existing contingency games. To this end, we propose a multi-branch contingency game model that accommodates phased intention disclosure, and introduce a cascaded consensus segmentation mechanism to progressively resolve and decouple intention uncertainty. Furthermore, a parallel solver based on the alternating direction method of multipliers (ADMM) is developed, leveraging scenario-level parallel computing to optimize trajectory planning efficiency. Experiments involving three strongly coupled agents demonstrate that the proposed approach outperforms conventional single-branch methods while significantly reducing the average solution time within a receding-horizon framework.

Abstract

Contingency games enable agents to anticipate and plan for other agents' hypothetical intents by constructing trajectories with a shared prefix and intent-dependent branches. While contingency games capture intent uncertainty, existing formulations rely on a single branching time, oversimplifying interactions in which different agents' intentions are revealed at different times. Moreover, the computational cost of such problems grows rapidly with the number of agents and intents, as all scenario-dependent best responses must be solved jointly. We introduce a multi-branch contingency architecture in which sources of intent uncertainty can be resolved progressively at different branching times, allowing the planned trajectories to adapt to the asynchronous revelation of intents. We also develop an ADMM-based solver that exploits scenario-level parallelism. Experiments on tightly coupled three-agent interactions support that the proposed architecture outperforms the conventional single-branch while achieving a lower mean receding-horizon solve time.

Problem

• contingency games
• multi-branch
• intent uncertainty
• asynchronous revelation
• computational cost

Innovation

• contingency games
• multi-branch architecture
• ADMM solver
• intent uncertainty
• asynchronous revelation