Temporal Intent Execution: Modeling Time-Dependent Goals and Future-Conditioned Internet Operations
Year: 2026
Type: preprint
Abstract: The evolution of intent-driven computing introduces the possibility of organizing digital capabilities around what users intend to accomplish rather than requiring them to manually identify and operate individual applications, websites, and services. However, most conventional interaction and task-execution models remain primarily oriented toward immediate requests. A user expresses an intention, the system interprets the request, selects appropriate capabilities, and attempts to execute the task within the current interaction. This approach is insufficient for intentions whose fulfillment depends on future dates, time intervals, external events, changing conditions, or temporal relationships between multiple operations. This paper proposes Temporal Intent Execution (TIE), a conceptual framework for representing, managing, activating, and executing human intentions across time. Rather than treating time as an external scheduling parameter attached to an already-defined task, TIE considers temporal conditions to be an intrinsic dimension of intent representation and execution. Under this perspective, an intention can specify not only what outcome is desired, but also when execution should occur, which future conditions should activate it, how long it should remain valid, what temporal dependencies must be satisfied, and under which circumstances execution should be postponed, modified, or terminated. To operationalize this perspective, the paper introduces a Temporal Intent Representation Model (TIRM) and a Temporal Intent Execution Architecture (TIEA). The proposed architecture comprises eight interconnected components: temporal intent acquisition, temporal intent representation, temporal condition interpretation, future-event observation, intent activation management, time-aware capability orchestration, execution monitoring and adaptation, and temporal completion and expiration management. It further distinguishes between time-triggered execution, event-triggered execution, condition-triggered execution, deferred execution, deadline-constrained execution, and temporally dependent multi-stage execution. A central contribution of this framework is the conceptual distinction between the temporal existence of an intention and the immediate execution of its associated operations. An intention may remain active without requiring continuous computation or immediate action. Its execution can be activated by a specified time, an externally observed event, a condition becoming satisfied, or a combination of these mechanisms. This separation potentially enables persistent, context-aware, and future-oriented Internet operations while reducing the need for users to repeatedly initiate, monitor, and coordinate tasks manually. The paper examines the relationship between TIE and existing research on temporal planning, temporal logic, event calculus, real-time scheduling, and autonomous task execution. It also investigates potential advantages concerning anticipatory assistance, reduced interaction overhead, temporal precision, task continuity, resource efficiency, cross-platform coordination, and deadline awareness. Finally, it develops research propositions, formalization requirements, evaluation scenarios, and implementation challenges. Importantly, this paper presents a conceptual research framework rather than a completed implementation or experimentally validated system. Its proposed advantages are theoretically motivated possibilities that require subsequent formal analysis and empirical evaluation.
Author: Zhang, Jincheng
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225593097