aiqbench analysis
Jagarin addresses the critical deployment paradox for mobile personal AI agents by introducing a three-layer architecture that balances battery efficiency with proactive duty management. The system utilizes on-device scoring to determine when hibernating agents should wake, while protocols like ARIA and ACE enable secure, machine-readable communication without relying on manual data entry or full email parsing. This approach represents a significant step forward in making persistent AI assistants viable on resource-constrained mobile devices without compromising privacy or battery life.
Jagarin: A Three-Layer Architecture for Hibernating Personal Duty Agents on Mobile
arXiv:2603.05069v3 Announce Type: replace Abstract: Personal AI agents face a deployment paradox on mobile: persistent background execution drains the battery and conflicts with platform background limits, yet purely reactive agents miss time-sensitive obligations until the user remembers to ask. We present Jagarin, a three-layer architecture that resolves this through structured hibernation and demand-driven wake. DAWN (Duty-Aware Wake Network) is an on-device scoring engine that runs on the platform's periodic wake and combines four signals (duty-typed optimal action windows, predicted user engagement, the cost of delay, and cross-duty batching) with per-duty adaptive thresholds to decide whether a sleeping agent should stay silent, nudge the user, or offer escalation. ARIA (Agent Relay Identity Architecture) is a commercial email identity proxy that turns institutional email into structured duty records and routes messages by category, removing manual data entry. ACE (Agent-Centric Exchange) is a protocol for machine-readable communication from institutions to personal agents, intended to make email parsing unnecessary in the long run. DAWN and ACE are specified and evaluated in companion papers; this paper describes how the three layers fit together and a working Flutter prototype on Android that combines them with an ephemeral cloud agent invoked only when the user asks. Behavioural signals, thresholds and scoring never leave the device, and every record ARIA extracts is sealed to the device's public key before it is stored, so the relay holds only ciphertext it cannot read. Cloud model exposure is limited to parsing commercial email and to user-initiated escalation, which receives only the structured duty record.
Abstract:Personal AI agents face a deployment paradox on mobile: persistent background execution drains the battery and conflicts with platform background limits, yet purely reactive agents miss time-sensitive obligations until the user remembers to ask. We present Jagarin, a three-layer architecture that resolves this through structured hibernation and demand-driven wake. DAWN (Duty-Aware Wake Network) is an on-device scoring engine that runs on the platform's periodic wake and combines four signals (duty-typed optimal action windows, predicted user engagement, the cost of delay, and cross-duty batching) with per-duty adaptive thresholds to decide whether a sleeping agent should stay silent, nudge the user, or offer escalation. ARIA (Agent Relay Identity Architecture) is a commercial email identity proxy that turns institutional email into structured duty records and routes messages by category, removing manual data entry. ACE (Agent-Centric Exchange) is a protocol for machine-readable communication from institutions to personal agents, intended to make email parsing unnecessary in the long run. DAWN and ACE are specified and evaluated in companion papers; this paper describes how the three layers fit together and a working Flutter prototype on Android that combines them with an ephemeral cloud agent invoked only when the user asks. Behavioural signals, thresholds and scoring never leave the device, and every record ARIA extracts is sealed to the device's public key before it is stored, so the relay holds only ciphertext it cannot read. Cloud model exposure is limited to parsing commercial email and to user-initiated escalation, which receives only the structured duty record.
Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Multiagent Systems (cs.MA)
arXiv:2603.05069 [cs.AI]
(or arXiv:2603.05069v3 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2603.05069 Focus to learn more arXiv-issued DOI via DataCite
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