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[CS.AI] Exploring Feedback-Coupled Memory Systems in Continuous Time

Published at: 2026-07-14 22:00 Last updated: 2026-07-15 01:59
#AI #Machine Learning #optimization

Abstract

The Feedback-Coupled Memory Systems (FCMS) architecture formalizes closed-loop coordination through four abstract operators, two of which - the agent update operator $f_i$ and the environmental update operator $\Psi$ - are left axiomatically undefined in the original framework. To address this, $f_i$ is defined by Mechanism-Based Intelligence (MBI), where agents update locally through a decentralized price mechanism and economic principles, and $\Psi$ is defined by the Coupled Memory Graph Process (CMGP), a non-Markovian framework where the environment is treated as a physical substrate that records and responds to trajectory history coherently without external forcing.

The resulting continuous-time FCMS instantiation achieves Lyapunov global dissipativity governed by the computable threshold $4\beta^2$.

Blogger's Review: This paper delves into the architecture of feedback-coupled memory systems, pushing the understanding of agent-environment interactions by defining key operators. This non-Markovian perspective offers a fresh approach to the design of intelligent systems, with broad application potential, especially in intelligent decision-making within dynamic environments.

Original Source: https://arxiv.org/abs/2607.09714

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