Enabling Reasoning with LegalRuleML

tags

LegalRuleML SPINdle

Notes

[RuleML] lacks support for the use of deontic concepts, such as obligations (such as achievement and maintenance), permission, prohibition, and is unable to handle cases with contrary-to-duty (CTD) obligations [6] that may arise from the violations of other obligations, which frequently appear in legal contracts

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transforming the legal norms represented using LegalRuleML into a variant of Modal Defeasible Logic

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use an implementation of DL as the engine to compute the extensions on the legal norms represented using LegalRuleML

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Modal Defeasible Logic: An Informal Introduction

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We define a defeasible theory D as a structure (F, R, >), where (i) F is a set of facts or indisputable statements, (ii) R is the set of rules, and (iii) > is an acyclic superiority relation on R.

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DL is a skeptical nonmonotonic logic meaning that it does not support con- tradictory conclusions. Instead, it seeks to resolve conflicts.

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r1 > r2 expresses that r1 overrides r2 if both rules are applicable

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A contract written in LegalRuleML is not intended to be executed directly, but the business logic can be transformed into a target language of a rule-based system to execute.

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ContractLog

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Semantics of Business Vocabulary and Business Rules (SBVR) [24] is an Object Management Group (OMG) standard to represent and fomalise business ontologies, including business rules, facts and business vocabularies.

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semantics for the deontic notions is underspecified.

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SBVR is based on classi- cal first-order-logic, which is not suitable to represent deontic notions and con- flicts. Also, it cannot handle contrary-to-duty obligations

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a theory in LKIF is a set of axioms and defeasible inference rules

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Legal- RuleML’s temporal notions of enforceability, efficacy and applicability cannot be represented with SBVR.

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