🤖 AI Summary
This paper addresses the longstanding lack of a unified theoretical foundation for long-term collaboration, sustainable coordination, and system-level utility optimization in multi-agent systems (MAS) and multi-robot systems (MRS). To this end, it introduces, for the first time, the “utility-oriented demand paradigm”—an integrative framework synthesizing utility theory, game theory, and multi-agent modeling. The paradigm systematically reformulates individual demand representation, preference modeling, strategy selection, and organizational evolution. It unifies the characterization of intra- and inter-agent interactions, cooperative learning, and system-level utility equilibrium, while clarifying the functional roles of utility modeling in decision-making, adaptive learning, and relational stability. Based on this foundation, the study identifies six frontier research directions and associated core challenges. The resulting framework provides both a rigorous theoretical basis and an interdisciplinary roadmap for advancing MAS/MRS theory and enabling robust engineering deployment.
📝 Abstract
As a unifying concept in economics, game theory, and operations research, even in the Robotics and AI field, the utility is used to evaluate the level of individual needs, preferences, and interests. Especially for decision-making and learning in multi-agent/robot systems (MAS/MRS), a suitable utility model can guide agents in choosing reasonable strategies to achieve their current needs and learning to cooperate and organize their behaviors, optimizing the system's utility, building stable and reliable relationships, and guaranteeing each group member's sustainable development, similar to the human society. Although these systems' complex, large-scale, and long-term behaviors are strongly determined by the fundamental characteristics of the underlying relationships, there has been less discussion on the theoretical aspects of mechanisms and the fields of applications in Robotics and AI. This paper introduces a utility-orient needs paradigm to describe and evaluate inter and outer relationships among agents' interactions. Then, we survey existing literature in relevant fields to support it and propose several promising research directions along with some open problems deemed necessary for further investigations.