On the Optimized Utilization of Smart Contracts in DLTs from the Perspective of Legal Representation and Legal Reasoning

Abstract

Smart contracts are computer programs stored in blockchain which
\nopen a wide range of applications but also raise some important issues. When we
\nconvert traditional legal contracts written in natural language into smart contracts
\nwritten in lines of code, problems will arise. Translation errors will exist in the
\nprocess of conversion since the law in natural language is ambiguous and imprecise,
\nfull of conflicts, and the emergence of new evidence may influence the processing
\nof reasoning. This research project has three purposes: the first aims at
\nthe resolution of these problems from logic and technical perspective to develop
\nthe accuracy and human-readability of smart contracts, by exploring a more novel
\nand advanced logic-based language to represent legal contracts, and analyzing an
\nextended argumentation framework with rich expressiveness; the second purpose
\nis to investigate various existing technologies like Akoma Ntoso and Legal-
\nRuleML, making the legal knowledge and reasoning machine-readable and be
\nlinked with the real world; third, to investigate the implementation of a mature
\nmulti-agent system incorporating the software agents with sensing, inferring,
\nlearning, decision-making and social abilities that can be fitted onto DLTs.