Seamless Integration of Knowledge Acquisition for Autonomous Systems by Domain Users with Prudence Capability
Abstract
Knowledge-based systems are typically constrained by their ability to acquire new knowledge without the intercession of a technical knowledge engineer. This introduces a fundamental disconnect between the system and the domain expert - even if a knowledge acquisition interface is provided, the domain expert is usually highly constrained in their expressiveness and ability to train the system due to technology-specific implementation.Knowledge-based systems are also currently limited in their applicability to autonomous systems. The domain expert/knowledge acquisition bottleneck in this paradigm also poses a great challenge to effectively train an autonomous system with new or modified behaviours without considerable effort and implementation change. In the autonomous system-operating environment, there is no consistent model of abstraction (of services/behaviour, information and data) that can be leveraged across different systems and domains.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 21, 2018
- Source ID
- FA23861614045
Entities
People
- Byeong Ho Kang
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Tasmania