Artifacts as Memory Beyond the Agent Boundary

Fuente: arXiv
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Main Authors: Martin, John D., Mince, Fraser, Saleh, Esra'a, Pajak, Amy
Format: Preprint
Published: 2026
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author Martin, John D.
Mince, Fraser
Saleh, Esra'a
Pajak, Amy
author_facet Martin, John D.
Mince, Fraser
Saleh, Esra'a
Pajak, Amy
contents The situated view of cognition holds that intelligent behavior depends not only on internal memory, but on an agent's active use of environmental resources. Here, we begin formalizing this intuition within Reinforcement Learning (RL). We introduce a mathematical framing for how the environment can functionally serve as an agent's memory, and prove that certain observations, which we call artifacts, can reduce the information needed to represent history. We corroborate our theory with experiments showing that when agents observe spatial paths, the amount of memory required to learn a performant policy is reduced. Interestingly, this effect arises unintentionally, and implicitly through the agent's sensory stream. We discuss the implications of our findings, and show they satisfy qualitative properties previously used to ground accounts of external memory. Moving forward, we anticipate further work on this subject could reveal principled ways to exploit the environment as a substitute for explicit internal memory.
format Preprint
id arxiv_https___arxiv_org_abs_2604_08756
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Artifacts as Memory Beyond the Agent Boundary
Martin, John D.
Mince, Fraser
Saleh, Esra'a
Pajak, Amy
Artificial Intelligence
The situated view of cognition holds that intelligent behavior depends not only on internal memory, but on an agent's active use of environmental resources. Here, we begin formalizing this intuition within Reinforcement Learning (RL). We introduce a mathematical framing for how the environment can functionally serve as an agent's memory, and prove that certain observations, which we call artifacts, can reduce the information needed to represent history. We corroborate our theory with experiments showing that when agents observe spatial paths, the amount of memory required to learn a performant policy is reduced. Interestingly, this effect arises unintentionally, and implicitly through the agent's sensory stream. We discuss the implications of our findings, and show they satisfy qualitative properties previously used to ground accounts of external memory. Moving forward, we anticipate further work on this subject could reveal principled ways to exploit the environment as a substitute for explicit internal memory.
title Artifacts as Memory Beyond the Agent Boundary
topic Artificial Intelligence
url https://arxiv.org/abs/2604.08756