A Defeasible Logic-based Framework for Contextualizing Deployed Applications

Abstract

In human to human communication, context increases the ability to convey ideas. However, in human to application and application to application communication, this property is difficult to attain. Context-awareness becomes an emergent need to achieve the goal of delivering more user-centric personalized services, especially in ubiquitous environments. However, there is no agreed-upon generic framework that can be reused by deployed applications to support context-awareness. In this paper, a defeasible logic-based framework for contextawareness is proposed that can enhance the functionality of any deployed application. The nonmonotonic nature of defeasible logic has the capability of attaining justifiable decisions in dynamic environments. Classical defeasible logic is extended by metarules to increase its expressiveness power, facilitate its representation of complex multi-context systems, and permit distributed reasoning. The framework is able to produce justified decisions depending on both the basic functionality of the system that is itself promoted by contextual knowledge and any crosscutting concerns that might be added by different authorities or due to further improvements to the system. Active concerns that are triggered at certain contexts are encapsulated in separate defeasible theories. A proof theory is defined along with a study of its formal properties. The framework is applied to a motivating scenario to approve its feasibility and the conclusions are analyzed using argumentation as an approach of reasoning.

A Multi-Agent Formalism Based on Contextual Defeasible Logic for Healthcare Systems

“…While in the second approach, a pair of rules were considered whose joint (de-)activation reproduced the observed inconsistency. In ( 8 ), the authors proposed a framework based on Contextual Defeasible Logic (CDL) for distributed MCS. The authors deployed the Meta-rules technique to perform reasoning on the system-acquired data.…”

“…This makes the overall system not provide a conclusion, causing it to become purposeless. This becomes a severe issue, especially in the safety-critical system dealing with life and death situations in healthcare systems ( 8 ).…”

“…After this, the system's conflicting information is dealt with using CDL ( 9 ). Contextual defeasible reasoning can handle inconsistencies occurring due to contradictory information ( 8 ).…”

Inmplode: A framework to interpret multiple related rule‐based models

“…Meta-rules are rules in which the prediction is another rule. It can be used to resolve a conflict, although the rule-based system may need more information about the context of the decision and new variables to support it (Al-Anbaki et al, 2019).…”