Researchers have proposed a formal model called Collective Counterfactual Planning (CCP) to describe how groups of agents can work together on projects despite individual limitations. The CCP model focuses on representational geometry, where each agent's perception and understanding of the task space is limited by its own subspace projection. This leads to four gates that determine whether a team can reach a common goal: implementation coalitions, conception, consent, and verification qualification. The researchers also define the Collective Counterfactual Solvability (CCS) problem, which separates geometric feasibility from executable attainment and validated completion. --- Why it matters: This work matters because it provides a framework for understanding how groups of agents with limited capabilities can still achieve complex goals. It has implications for areas like multi-agent systems, distributed planning, and human-AI collaboration, where individual agents may have different perspectives or limitations. Source: https://arxiv.org/abs/2608.17932