Cognifold: Always-On Proactive Memory via Cognitive Folding

• URL: http://arxiv.org/abs/2605.13438v1
• Date: Wed, 13 May 2026 12:34:39 GMT
• Title: Cognifold: Always-On Proactive Memory via Cognitive Folding
• Abstract summary: CogniFold is a brain-inspired "always-on" agent memory designed for the next generation of proactive assistants.<n>We ground this by extending Complementary Learning Systems theory from two layers (hippocampus, neocortex) to three, adding a prefrontal intent layer.<n>We evaluate structural formation using CogEval-Bench, demonstrating that CogniFold uniquely produces memory structures that match cognitive expectations.
• Score: 15.403868103736556
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Existing agent memory remains predominantly reactive and retrieval-based, lacking the capacity to autonomously organize experience into persistent cognitive structure. Toward genuinely autonomous agents, we introduce Cognifold, a brain-inspired "always-on" agent memory designed for the next generation of proactive assistants. CogniFold continuously folds fragmented event streams into self-emerging cognitive structures, bootstrapping progressively higher-level cognition from incoming events and accumulated knowledge. We ground this by extending Complementary Learning Systems (CLS) theory from two layers (hippocampus, neocortex) to three, adding a prefrontal intent layer. Emulating the prefrontal cortex as the locus of intentional control and decision-making, CogniFold achieves this through graph-topology self-organization: cognitive structures proactively assemble under the stream, merge when semantically similar, decay when stale, relink through associative recall, and surface intents when concept-cluster density crosses a threshold. We evaluate structural formation using CogEval-Bench, demonstrating that CogniFold uniquely produces memory structures that match cognitive expectations and concept emergence. Furthermore, across 7 broad-coverage benchmarks spanning five cognitive domains, we validate that CogniFold simultaneously performs robustly on conventional memory benchmarks.

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