中国青年报客户端讯（中青报·中青网记者 王璟瑄）12月26日，2025年度"龚育之—孙小礼科哲青年著作 奖"颁奖典礼暨学术报告会在北京大学李兆基人文学苑举行。此次评选共收到15部提名或自荐著作，其 中，中山大学哲学系副教授方卫的《生物学的解释自主性》和内蒙古师范大学科学技术史研究院副教授 陈志辉的《融"西"继"绝"：乾嘉天算专门之学论稿》脱颖而出，斩获殊荣。 来源：中国青年报客户端 据了解，该奖项以龚育之、孙小礼二位先生命名，由北京大学哲学系于2025年9月正式设立，旨在纪念 两位学界前辈为学科发展作出的开创性贡献，增进青年学者的研究热情，推动我国科技哲学学科建设发 展。该奖项面向40周岁以下中国籍青年学者，每年评审一次，每次奖励1至2部近四年内出版的科技哲学 领域的高水平著作。评奖范围涵盖科学哲学与技术哲学、科学技术与社会（含科技伦理）、科学技术 史、逻辑学等分支领域。 ...

Core Viewpoint - The article presents the Generalized Agent Theory, which aims to unify concepts from artificial intelligence, physics, and philosophy by establishing a framework that connects the roles of "observers" in physics with "agents" in AI [1][2][27]. Group 1: Development of Generalized Agent Theory - The exploration of Generalized Agent Theory began in 2014, initially assessing the intelligence levels of humans and AI systems, leading to the establishment of a standard agent model [4]. - Over the years, intelligence tests were conducted, showing significant advancements in AI, with the highest scoring AI surpassing the intelligence level of a 14-year-old by 2024 [4]. - The theory identifies two extreme states of intelligence: Alpha agents (zero intelligence) and Omega agents (infinite intelligence), introducing concepts of Alpha and Omega forces that drive agent evolution [5][6]. Group 2: Theoretical Framework of Generalized Agent Theory - The theory comprises a standard agent model, evolutionary dynamics (intelligent fields, intelligent gravity, and "wisdom"), classifications of different intelligence levels (three main categories and 243 subtypes), and 18 types of multi-agent relationships [7]. - The standard agent model is built on five fundamental functional modules: information input, information output, dynamic storage, information creation, and control function [8][10]. - The five basic functions define an agent's essence and are measured in a five-dimensional capability vector space, allowing for a systematic classification of all potential agents [11][12]. Group 3: Multi-Agent Relationships - The theory analyzes multi-agent relationships through three dimensions: perception relationships, communication relationships, and interaction relationships, leading to a comprehensive understanding of agent interactions [13][14]. Group 4: Intelligent Fields and Gravity - The "extreme point intelligent field model" is introduced to describe the evolutionary dynamics of agents, characterized by Alpha decay fields and Omega enhancement fields [15][16]. - The net intelligent evolution field represents the combined effect of these two forces on an agent's evolution [16]. Group 5: Wisdom as an Intrinsic Property - "Wisdom" is defined as a dynamic measure of an agent's overall information processing capability, influenced by the synergy of its five core functions [17]. - The theory highlights two key effects of wisdom: the Matthew effect, where higher wisdom leads to faster capability growth, and the resilience effect, where higher wisdom enhances resistance to decline [17]. Group 6: Implications for AI and Philosophy - The Generalized Agent Theory provides new insights into fundamental questions in AI, defining intelligence as the overall effectiveness and adaptability of an agent under the influence of Alpha and Omega fields [18]. - It also reinterprets the concept of consciousness as the control function of an agent, distinguishing between self-awareness and awareness of others based on the source of control commands [18]. Group 7: Insights into Physics - The theory offers a new perspective on the relationship between observers in physics and agents, suggesting that the universe can be viewed as a complex generalized agent evolving between Alpha and Omega states [19]. - It explains the differences among classical mechanics, relativity, and quantum mechanics as arising from the varying capabilities of observer agents [20][21][23]. - The concept of entropy is redefined as a measure of information loss related to the observer's capabilities, linking it to the dynamics of intelligent agents [24][25][26]. Group 8: Conclusion - The Generalized Agent Theory aims to provide a unified theoretical foundation for fragmented research in intelligent sciences, potentially reconciling contradictions between general relativity and quantum mechanics [27].