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

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