A Modular Cognitive Model for Solving Complex Problems Based on "Memory Fragments"

The "Memory Fragments" model represents an innovative modular cognitive architecture engineered for complex problem resolution. This architecture integrates sequential logic with conditionally activated knowledge modules, termed "fragments," drawing inspiration from the organization of human memory systems. This approach facilitates contextually relevant reasoning through the selective retrieval of pertinent information at pertinent junctures within the problem-solving process. Addressing limitations inherent in traditional chain-of-thought methodologies, such as high token consumption and the generation of generalized responses, this model presents a more efficient, adaptable, and contextually sensitive framework. Its utility spans applications encompassing logistics, education, and technological optimization. This architecture constitutes a significant advancement in the development of intelligent systems characterized by dynamic reasoning capabilities and the capacity for precision-driven solutions.