Cognitive modeling, which explores the essence of cognition, including motivation, emotion, and perception, has been widely applied in the artificial intelligence (AI) agent domains, such as robotics. From the computational perspective, various cognitive functionalities have been developed through utility theory to provide a detailed and process-based understanding for specifying corresponding computational models of representations, mechanisms, and processes. Especially for decision-making and learning in multi-agent/robot systems (MAS/MRS), a suitable cognitive 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. This survey examines existing robotic systems for developmental cognitive models in the context of utility theory. We discuss the evolution of cognitive modeling in robotics from behavior-based robotics (BBR) and cognitive architectures to the properties of value systems in robots, such as the studies on motivations as artificial value systems, and the utility theory based cognitive modeling for generating and updating strategies in robotic interactions. Then, we examine the extent to which existing value systems support the application of robotics from an AI agent cognitive modeling perspective, including single-agent and multi-agent systems, trust among agents, and human-robot interaction. Finally, we survey the existing literature of current value systems in relevant fields and propose several promising research directions, along with some open problems that we deem necessary for further investigation.

翻译：认知建模旨在探究认知的本质，包括动机、情感与感知，已在人工智能体领域（如机器人学）得到广泛应用。从计算视角出发，各类认知功能通过效用理论得以发展，为构建表征、机制与过程的相应计算模型提供了细致且基于过程的理解。特别是在多智能体/机器人系统的决策与学习中，合适的认知模型能引导智能体选择合理策略以满足当前需求，学习协作与行为组织，从而优化系统效用，建立稳定可靠的关系，并保障每个群体成员的可持续发展——这与人类社会的运作模式相似。本综述在效用理论框架下检视了现有机器人系统中发展性认知模型的研究进展。我们探讨了机器人学中认知建模的演进脉络：从基于行为的机器人学到认知架构，进而延伸至机器人价值系统的特性研究，包括作为人工价值系统的动机研究，以及基于效用理论、用于生成与更新机器人交互策略的认知建模。随后，我们从人工智能体认知建模的视角，评估现有价值系统对机器人应用的支持程度，涵盖单智能体与多智能体系统、智能体间信任及人机交互等方面。最后，我们系统梳理了相关领域当前价值系统的现有文献，提出了若干具有前景的研究方向，并指出了一些我们认为亟待深入探索的开放性问题。