Chung-Lun Lie

National Taiwan University of Science and Technology

Papers

Total Citations

H-Index

About

Chung-Lun Lie is a researcher whose work bridges artificial intelligence, logic programming, and deontic reasoning, with a particular focus on developing formal frameworks for decision-making in dynamic systems. His most cited paper, "Defeasible Deontic Control for Discrete Events Based on EVALPSN" (2004), has garnered 10 citations and introduces a novel approach to handling normative and defeasible reasoning in discrete event control. This work extends the EVALPSN (Extended Vector Annotated Logic Program with Strong Negation) paradigm, offering a robust method for modeling permissions, obligations, and exceptions in automated systems. Lie’s contributions are significant for advancing the theoretical underpinnings of deontic logic in AI, particularly for applications in robotics, autonomous agents, and safety-critical systems where ethical and legal constraints must be dynamically managed. While his citation count reflects a focused niche, his research provides foundational tools for integrating normative reasoning into computational models, influencing subsequent work in defeasible reasoning and control theory. Lie’s achievements highlight the importance of formal logic in creating reliable, rule-based AI systems, making his work a valuable reference for students and researchers exploring the intersection of logic, ethics, and automation.