Outcome-Grounded Adaptive Cognitive Scheduling in Heterogeneous Agentic Systems

This working paper introduces the Adaptive Cognitive Scheduling Hypothesis (ACSH) and documents AVCOS as a design-science pilot for outcome-grounded orchestration of heterogeneous AI resources. The central research question is whether a learned cognitive scheduler can improve externally verified system utility by dynamically allocating tasks across language models, specialist models, deterministic tools, retrieval systems, knowledge graphs, validators, and human escalation paths. The proposed framework combines learned routing, sparse activation, calibrated worker selection, error-correlation penalties, value-of-computation stopping rules, three-layer micro-validation (syntactic, semantic, and pragmatic-economic), and explicit failure-control mechanisms through independent Doctor and Contrarian roles. AVCOS serves as the pilot environment because autonomous enterprise operation provides persistent, heterogeneous tasks with real execution states, delayed feedback, resource constraints, recovery requirements, and externally observable economic outcomes. The paper explicitly distinguishes internal system success from external execution truth and introduces evaluation measures including Pareto Efficiency Score, Cascade Failure Rate, confidence calibration, falsification yield, false-alarm rate, and externally verified business outcomes. The work does not claim that AVCOS has already demonstrated superiority over frontier AI models. Instead, it presents a falsifiable research hypothesis, a formal scheduling framework, an instrumented pilot architecture, and a two-track experimental programme. Track 1 evaluates adaptive scheduling against round-robin and static capability routing under zero-cost constraints. A separate future Track 2 is reserved for controlled comparison with a named frontier model. AVCOS is designed and operated by the author. Pilot telemetry reported in the paper is currently unpublished and has not been independently audited. The paper therefore treats the current system observations as motivating evidence rather than empirical confirmation of the ACSH.