Inferring Group Intent as a Cooperative Game. An NLP-based Framework for Trajectory Analysis
arXiv:2510.23905v2 Announce Type: replace-cross Abstract: This paper studies group target trajectory intent as the outcome of a cooperative game where the complex-spatio trajectories are modeled using an NLP-based generative model. In our framework, the group intent is specified by the characteristic function of a cooperative game, and allocations for players in the cooperative game are specified by either the core, the Shapley value, or the nucleolus. The resulting allocations induce probability distributions that govern the coordinated spatio-temporal trajectories of the targets that reflect
This research builds on recent advancements in large language models and game theory, applying them to complex multi-agent systems, aligning with the ongoing acceleration in AI research capabilities.
This framework offers a novel approach to understanding and predicting coordinated group behavior, which has significant implications for AI agents, multi-robot systems, and autonomous defense applications.
The ability to infer group intent through a cooperative game model, utilizing NLP-based generative models for trajectory analysis, provides a more sophisticated tool for predicting and influencing collective actions of autonomous entities.
- · AI developers
- · Robotics companies
- · Defense contractors
- · Logistics and supply chain management
- · Traditional surveillance methods
- · Purely reactive autonomous systems
Improved coordination and predictability in multi-agent systems, leading to more robust autonomous operations.
Enhanced capabilities for strategic planning and counter-strategy development in dynamic environments, with both civilian and military implications.
The potential for AI systems to not only infer but also subtly influence, or even dictate, group intent in complex scenarios, raising ethical and control challenges.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.LG