Intent Assurance

Intent assurance focuses on reliably translating high-level user intentions (intents) into effective actions within complex systems, particularly in networking and AI-driven dialogue. Current research emphasizes developing robust methods for intent processing, conflict resolution among competing intents, and continuous verification of intent fulfillment, often employing machine learning techniques like reinforcement learning, contrastive learning, and large language models. This field is crucial for advancing automation in diverse applications, improving the reliability and efficiency of network management, and enhancing human-computer interaction in task-oriented systems.