The Stochastic Gap: A Markovian Framework for Pre-Deployment Reliability and Oversight-Cost Auditing in Agentic Artificial Intelligence

1. 1Develop a measure-theoretic Markov framework to model stochastic policies
2. 2Analyze the framework's ability to provide statistical support and local unambiguity
3. 3Apply the framework to pre-deployment reliability and oversight-cost auditing in agentic AI
4. 4Evaluate the economic governability of the resulting trajectory

AI engineers and researchers benefit from this framework as it helps ensure reliability and governability of agentic AI systems, while product managers and entrepreneurs can use it to optimize oversight costs

💡 A stochastic gap exists between deterministic workflows and stochastic policies in agentic AI, requiring a new framework for reliability and oversight-cost auditing

🤖 New Markovian framework for agentic AI reliability and oversight-cost auditing