From Memory to Topology A Journey Through Human Recollection and Computational Representation
$ 45.5
Description
Based on the framework introduced in the paper Memory Encoding Is All We Need (SSRN 5339881), this book bridges human experience, cognitive science, and formal mathematics to present a new understanding of memory and its computational representation. It begins by exploring the origins of memory: how early humans learned to encode experiences not as static records, but as structured, meaning-linked traces shaped by survival, emotion, and sensory details. It explains that memory is not stored in a linear or chronological way, but forms a connected network where "closeness" is defined by similarity of feeling, sensation, or subjective time — a natural form of topology. The book then critiques traditional models that treat memory as exact storage, showing they fail to explain the common experience of partial, fragmented recollection. It introduces the symbolic-emotional hypothesis: every memory can be described as a unit ζ, composed of emotional state, internal time, sensory features, intensity, and behavioral impact. These units exist in a metric topological space Z, where distance between memories is calculated based on weighted similarities across these dimensions. This framework is formalized through a graph structure, where memories are nodes and connections are weighted links representing relationships like emotional transition or temporal adjacency. A core concept is the retrieval function R: given a partial cue, it identifies related memories in the topological neighborhood and combines them to reconstruct a complete, coherent recollection — mirroring how the human mind interpolates missing details. The work also outlines practical computational encoding, showing how memory units and their connections can be represented in structured formats, and describes a step-by-step process for traversal and reconstruction. Through a case study of childhood memory reconstruction, it demonstrates how the model works in practice. Finally, it highlights wide-ranging applications: Artificial Intelligence: Enabling systems with context awareness, emotional coherence, and autobiographical identity.