A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

View the PDF file from the paper entitled “A Comprehensive Survey” for advanced artificial intelligence factors: new institutions for lifelong mediation and systems, written by Jinyuan Fang and 14 other authors

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a summary:Recent developments in large language models have raised increasing interest in artificial intelligence factors capable of solving complex tasks in the real world. However, most of the current agents systems depend on handcrafted configurations that are still fixed after publication, which limits their ability to adapt to dynamic and advanced environments. To this end, recent research has explored the techniques of delegations of agents that aim to improve agent systems automatically based on interaction data and environmental comments. This emerging trend sets the basis for artificial intelligence agents, who record the fixed capabilities of the basic models with the continuous ability to adapt required by lifelong systems. In this poll, we offer a comprehensive review of the current technologies of self -evolving agents. Specifically, we first offer a unified conceptual frame that wounds the residual feeding ring behind the design of self -development agent systems. The frame highlights four main components: system inputs, agent, environment, and improved, which work as a basis for understanding and comparing various strategies. Based on this framework, we review a wide range of self -development techniques that target different components of the agent system. We are also looking for development strategies for the field that have been developed for specialized fields such as biomedic, programming and financing, as the improvement goals are tightly associated with field restrictions. In addition, we offer a dedicated discussion on evaluation, safety and ethical considerations of self -advanced client systems, which are essential to ensure their effectiveness and reliability. This survey aims to provide researchers and practitioners with a systematic understanding of advanced artificial intelligence agents, and to lay the foundation for the development of the most adaptive, self -and -life systems, and lifelong factors.