Core Viewpoint - The article presents the "Generalized Agent Theory," proposing that the universe is a dynamic evolving agent, and agents are the fundamental units of the universe. This theory provides a new paradigm for understanding the universe's cognitive level and its profound impact on various fields such as physics, technology philosophy, and intelligent science [2][4][5]. Summary by Sections 1. Introduction to Generalized Agent Theory - Generalized Agent Theory, established in 2014, has undergone ten years of research and iteration, resulting in nearly ten published papers. By 2025, it has developed a framework consisting of four core modules: standard agent model, agent classification system, extreme point intelligent field model, and multi-agent relationship system [6][8]. 2. Structure of the Standard Agent Model - The standard agent model serves as the foundation of the theory, positing that any agent is fundamentally an information processing system composed of five essential functional modules: information input, information output, dynamic storage, information creation, and a control module coordinating the first four [8][10]. 3. Classification of Agents - Agents are classified into three types based on their functional capabilities: 1. Absolute zero agent (Alpha agent) with all functions at zero 2. Omniscient agent (Omega agent) with all functions at infinity 3. Finite agent with functions neither at zero nor infinity [10][11]. 4. Theoretical Implications - The first key implication is that the universe itself is a dynamic evolving agent, with the Omega agent representing a state of omniscience. If any part of the universe degrades from this state, it becomes a composite system of finite and absolute zero agents [11][12]. - The second implication is that the evolution of agents is driven by two fundamental forces: Alpha gravity, which drives agents towards the Alpha state, and Omega gravity, which drives them towards the Omega state. These forces create a field effect throughout the universe [12][13]. 5. Unique Value of Different Agent Levels - The framework allows for the exploration of three distinct models of the universe: 1. Absolute zero intelligence universe, serving as a logical starting point for analysis 2. Infinite intelligence universe, providing a perspective for conceptual integration and theoretical unification 3. Finite intelligence universe, aligning closely with the reality observed by humans [15][17]. 6. Understanding Uncertainty and Time-Space - The theory posits that the essence of entropy is closely related to the observer's intelligence level, suggesting that entropy arises from the limitations of finite observers in tracking all microstates. This leads to an increase in information loss, which is perceived as entropy [19][20]. 7. Unifying Physical Theories - The differences among the three major physical theories (classical mechanics, relativity, and quantum mechanics) stem from the intelligence levels of their observers. The theory proposes a spectrum of intelligence levels that can explain the variations in physical phenomena observed under different conditions [21][25]. 8. Conclusion - The article emphasizes the need for further exploration of foundational scientific concepts and their intrinsic relationships with the intelligence levels of the universe and observers, indicating that many important theoretical issues await in-depth research [26][28].

Core Viewpoint - The article introduces the "Generalized Agent Theory" (GAT), which proposes that all entities, including physical systems, life, and AI, can be viewed as "agents" and suggests a potential pathway towards a "Theory of Everything" [1][3][28]. Group 1: Theory of Everything - The "Theory of Everything" aims to create a unified framework that explains all phenomena in the universe using minimal foundational laws, from the Big Bang to the emergence of intelligence and self-awareness [2]. - The pursuit of this theory faces significant challenges, particularly the incompatibility between general relativity and quantum mechanics, as well as the lack of a unified theory for the four fundamental forces of physics [4][8]. Group 2: Generalized Agent Theory - The GAT is built on the exploration of the core concept of "agents" in AI, leading to the development of a unified structure that encompasses various systems, including physical, biological, and AI systems [3][6]. - The theory identifies three main goals: unifying the four fundamental forces, integrating general relativity with quantum mechanics, and consolidating physical, biological, and AI systems into a single theoretical model [28]. Group 3: Core Components of GAT - GAT consists of four core components: the standard agent model, agent classification system, extreme point intelligent field model, and multi-agent relationship system [10][19]. - The standard agent model defines agents as information processing systems with five essential functional modules: information input, output, dynamic storage, information creation, and a control module [12][18]. Group 4: Challenges and Hypotheses - The theory proposes that the four fundamental forces may be manifestations of a more fundamental "intelligent field" that drives the evolution of all agents [7][41]. - It suggests that the differences in classical mechanics, relativity, and quantum mechanics arise from the varying intelligence levels of observers, which can be adjusted as a parameter in theoretical scenarios [46][52]. Group 5: Implications and Future Directions - GAT opens new avenues for exploring the fundamental questions of the universe, emphasizing that it is not a closed theory but an exploratory framework that may lead to deeper scientific inquiries [54][57]. - The theory's potential to unify various scientific disciplines under the concept of agents could provide valuable insights into the nature of existence and intelligence [42][56].

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].

Group 1 - The article discusses two major challenges in 21st-century science: the unification of general relativity and quantum mechanics, and the essence of intelligence and consciousness [1] - The rapid development of artificial intelligence presents unprecedented opportunities to address these challenges [1] - The theory of general intelligent agents proposed by Dr. Liu Feng and professors from the University of Science and Technology of China aims to explore key issues in physics, artificial intelligence, and the philosophy of technology [1] Group 2 - The article highlights a paradigm shift in foundational science, likening it to the transition from the geocentric model to the heliocentric model, with intelligent agents poised to drive this profound change [1] - The event on May 10 features Dr. Liu Feng sharing insights on the core position of intelligent agents in the scientific paradigm shift of the 21st century, with commentary from Professor Yang Yingrui and hosted by Wang Junxiu [1]