Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Artificial Intelligence (AI) has long dealt with the issue of finding a suitable formalization for commonsense reasoning. Defeasible argumentation has proven to be a successful approach in many respects, proving to be a con- fluence point for many alternative logical frameworks. Dierent formalisms have been developed, most of them sharing the common notions of argument and warrant. In defeasible argumentation, an argument is a tentative (de- feasible) proof for reaching a conclusion. An argument is warranted when it ultimately prevails over other conflicting arguments. In this context, defeasi- ble consequence relationships for modelling argument and warrant as ll as their logical properties have gained particular attention. This article analyzes two non-monotonic inference operators Carg and Cwar intended for modelling argument construction and dialectical analysis (warrant), respectively. As a basis for such analysis  will use the LDSar framework, a unifying approach to computational models of argument using Labelled Deductive Systems (LDS). In the context of this logical framework,  show how labels can be used to represent arguments as ll as argument trees, facilitating the definition and study of non-monotonic inference op- erators, whose associated logical properties are studied and contrasted.  contend that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworks. Mathematics Subject Classification (2000). Primary 03B22; Secondary 03B42.
['Carlos Iván Chesñevar', 'Guillermo Ricardo Simari']
I am writing a research paper on a idea Modelling Inference in Argumentation through Labelled Deduction: Formalization and Logical Properties
[{"from": "human", "value": "I am writing a research paper on a idea Modelling Inference in Argumentation through Labelled Deduction: Formalization and Logical Properties"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Artificial Intelligence (AI) has long dealt with the issue of finding a suitable formalization for commonsense reasoning. Defeasible argumentation has proven to be a successful approach in many respects, proving to be a con- fluence point for many alternative logical frameworks. Dierent formalisms have been developed, most of them sharing the common notions of argument and warrant. In defeasible argumentation, an argument is a tentative (de- feasible) proof for reaching a conclusion. An argument is warranted when it ultimately prevails over other conflicting arguments. In this context, defeasi- ble consequence relationships for modelling argument and warrant as ll as their logical properties have gained particular attention. This article analyzes two non-monotonic inference operators Carg and Cwar intended for modelling argument construction and dialectical analysis (warrant), respectively. As a basis for such analysis  will use the LDSar framework, a unifying approach to computational models of argument using Labelled Deductive Systems (LDS). In the context of this logical framework,  show how labels can be used to represent arguments as ll as argument trees, facilitating the definition and study of non-monotonic inference op- erators, whose associated logical properties are studied and contrasted.  contend that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworks. Mathematics Subject Classification (2000). Primary 03B22; Secondary 03B42."}]