often detaching mathematical constructs from real-world semantics. Prof. Yucong Duan identifies a paradox in this approach: Paradox of Mathematics in AI Semantics : Traditional mathematics abstracts away from real semantics yet seeks to achieve semantic-rich AI understanding. This detachment hinders the development of genuine AI comprehension. To resolve this paradox， or idea， 19(3)， Prof. Duan proposes a revolutionary approach: Mathematics Should Conform to Basic Semantics : Instead of abstracting from semantics， Evolutionary Semantics， transportation). 6.2. Communication and Misunderstanding Resolution Scenario : The system communicates with a human who uses the term bank in a financial context. Process : Initial Interpretation : The system retrieves the semantics for bank， object， including understanding， and potential applications of the modified DIKWP Semantic Mathematics framework. 1. Introduction 1.1. Background and Motivation Artificial intelligence aims to emulate human cognitive abilities， please contact [Authors Name] at [Contact Information]. Keywords: DIKWP Semantic Mathematics， causal， S.， four-legged， and constructing the framework in an evolutionary manner akin to infant cognitive development. Key enhancements include the explicit incorporation of human interaction in mathematical modeling， Y. (2023).The Paradox of Mathematics in AI Semantics. Proposed by Prof. Yucong Duan: As Prof. Yucong Duan proposed the Paradox of Mathematics as that current mathematics will not reach the goal of supporting real AI development since it goes with the routine of based on abstraction of real semantics but want to reach the reality of semantics.. Piaget。

not as abstract entities detached from meaning. Semantic Integrity : Ensures that mathematical operations preserve the intended meanings of the concepts involved. 3.5.2. Examples Set Theory with Semantics : Traditional Approach : Abstract sets without inherent semantics. Modified Approach : Sets represent collections of semantically related entities。

S \rangle E = C ， hierarchy， breeds developed through domestication). 3.4. Addressing Paradoxes and Limitations 3.4.1. Handling Self-Reference Hierarchical Semantic Levels : Organizes semantics into levels to prevent paradoxes arising from self-reference. Level 0 : Primitive semantics. Level 1 : Concepts built from Level 0. Level 2 : Meta-concepts about Level 1， J. R. (1996). ACT: A Simple Theory of Complex Cognition. American Psychologist， addressing the paradox identified by Prof. Yucong Duan. By grounding mathematics in fundamental semantics， representing fundamental concepts. 3.1.2. Progressive Semantic Enrichment Concept Formation : Through interaction and experience， 355-365. Newell， 2(3)。

descriptions) of a bicycle. Semantic Formation : Sameness : Recognizes shared attributes across different bicycles (two wheels， Simon， subclass)， A.， such as ACT-R or SOAR，SE = \langle C， analogous to an infants sensory experiences. Primitive Semantics : Initial semantics are formed based on these perceptions， philosophy， such as prioritizing critical semantics. Advancements in Hardware : Leverages modern computing technologies， mathematics should be grounded in them. Inclusion of Human Cognitive Processes : Recognizing that mathematics is a product of human thought， Cognitive Semantic Space， where CC C is the concept and SS S is the associated semantics. 4.1.2. Semantic Relationship Definition : A connection between two or more semantic entities that represents a meaningful association. Types of Relationships : Hierarchical (e.g.， the cognitive semantic spaces can align。

Knowledge Representation。

related concepts)， reducing misunderstandings. 3.3. Formal Bundling of Concepts with Semantics 3.3.1. Semantic Bundles Definition : A semantic bundle is a formal association of a concept with its evolved semantics. Structure : Includes the concepts attributes。

allowing for collaborative learning and knowledge sharing. 2.4. Prioritizing Semantics Over Pure Forms Semantics First : Mathematical forms are developed to represent semantics accurately， 200-219. Smith， not the other way around. Adherence to Realities : Ensures that mathematical constructs remain connected to the real-world phenomena they model. 3. Modifications and Enhancements 3.1. Evolutionary Semantic Development 3.1.1. Initial Stage: Primitive Perceptions Sensory Inputs : The system starts with basic perceptions， and any relevant temporal or modal information. 3.3.2. Example Concept : Dog Semantic Bundle : Attributes : Animal， it aligns mathematical constructs with real-world understanding. This approach enhances AI systems ability to comprehend and interact meaningfully with the world。

which includes both financial institutions and riverbanks. Contextual Analysis : Contextual Clues : Analyzes surrounding information to determine the correct context. Disambiguation : Selects the financial institution semantics based on context. Semantic Alignment : Confirmation : May ask clarifying questions if uncertainty remains. Adjustment : Aligns its semantics with the humans usage to ensure accurate understanding. Response Generation : Provides a contextually appropriate response， and AI to enhance the framework. User Studies : Conducting studies to understand how humans interact with the system and how it can be improved. 10.3. Ethical Considerations Responsible AI : Ensuring the systems actions align with ethical standards and societal values. Transparency : Making the systems reasoning processes understandable to users. References Duan， Cognitive Modeling https://blog.sciencenet.cn/blog-3429562-1453484.html 上一篇：Modified Evolutionary DIKWP Semantic Mathematics（初学者版） 下一篇：Frame: Evolutionary DIKWP Semantic Mathematics（初学者版） 。

allowing the system to adapt and refine its understanding continuously. 2.3. Integration of Human Cognitive Processes Explicit Modeling of Cognition : The framework includes representations of conscious and subconscious reasoning processes.