Industry Monitor Humanoid Industrial & Cobot AGV / AMR Quadruped Reducers · Servos · Sensors Drones & Autonomy Embodied AI
Robos News
Robotics

Minimal Recurrent Behavioral Memory for Imitation under Partial Observability

arXiv:2609.25757v1 Announce Type: cross Abstract: What is the least recurrent memory needed to reproduce a specified expert under partial observability? The instantaneous requirement is the conditional entropy of the expert's behavioral quotient, but recurrence must also preserve distinctions that future observations will not restore before use. We characterize this minimal recurrent behavioral memory by a compatibility relation: under transitivity its classes attain the exact minimum, while th

Published September 23, 2026 · Category: Robotics

Overview

arXiv:2609.25757v1 Announce Type: cross Abstract: What is the least recurrent memory needed to reproduce a specified expert under partial observability? The instantaneous requirement is the conditional entropy of the expert's behavioral quotient, but recurrence must also preserve distinctions that future observations will not restore before use. We characterize this minimal recurrent behavioral memory by a compatibility relation: under transitivity its classes attain the exact minimum, while the general case is an entropy minimization over closed compatible state assignments, with exact certificates on finite instances. A sole-carrier measurement protocol separates behavioral sufficiency, excess code rate, and information carried by observations or other memory paths; experimental bit requirements refer to the induced symbolic behavioral model under the stated occupancy. Across manipulation tasks, learned code rates remain near zero- and two-bit requirements as hidden modes grow to $512$, and anticipatory memory follows a $2\to1\to0$ requirement despite zero instantaneous demand during waiting. Learning this representation remains difficult: event-agnostic future-behavior supervision yields $36/40$ sufficient seeds with one frozen configuration and improves the longest-horizon pixel setting from $0/8$ to $6/8$ sufficient held-out seeds (closed-loop success from $0.08$ to $0.57$). On unmodified community benchmarks, the protocol certifies delay-independent requirements, which sufficient codes match at mid-delay. The supervision aids commitment but can induce predictive surplus; annealing it lets imitation and rate training reduce that surplus, separating the information-theoretic target from the ability to learn it.

Source

Originally published at arxiv.org.

Related Articles

Robos News Newsroom

Robos News reports on robotics research, components, manufacturers, field deployments, and industrial automation worldwide. Tip our newsroom: [email protected]

Email the newsroom →
Reporting standard: Product specifications, deployment counts, and performance claims are attributed to their source. Safety-critical decisions should be based on the applicable technical documentation and validation for the operating environment.
More from News →