Defeasible Reasoning and Argument-Based Systems in Medical Fields: An Informal Overview

Longo, Luca; Dondio, Pierpaolo

doi:10.1109/cbms.2014.126

Cited by 13 publications

(6 citation statements)

References 30 publications

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“…Future works will be focused on the replication of the approach adopted in this study using other knowledge bases elicited from other MWL experts. Additionally, this approach will be extended incorporating fuzzy representation of rules and acceptability semantics, borrowed from argumentation theory [2,14], with the aim of improving conflict resolution of rules and building models expected to have an even higher sensitivity and validity. Table 4.…”

Section: Discussionmentioning

confidence: 99%

Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile

Rizzo¹,

Dondio²,

Delany³

et al. 2016

IFIP Advances in Information and Communication Technology

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In the last few decades several fields have made use of the construct of human mental workload (MWL) for system and task design as well as for assessing human performance. Despite this interest, MWL remains a nebulous concept with multiple definitions and measurement techniques. State-of-the-art models of MWL are usually ad-hoc, considering different pools of pieces of evidence aggregated with different inference strategies. In this paper the aim is to deploy a rule-based expert system as a more structured approach to model and infer MWL. This expert system is built upon a knowledge-base of an expert and translates into computable rules. Different heuristics for aggregating these rules are proposed and they are elicited using inputs gathered in an user study involving humans performing web-based tasks. The inferential capacity of the expert system, using the proposed heuristics, is compared against the one of two ad-hoc models, commonly used in psychology: the NASA-Task Load Index and the Workload Profile assessment technique. In detail, the inferential capacity is assessed by a quantification of two properties commonly used in psychological measurement: sensitivity and validity. Results show how some of the designed heuristics can over perform the baseline instruments suggesting that MWL modelling using expert system is a promising avenue worthy of further investigation.

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Section: Discussionmentioning

confidence: 99%

Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile

Rizzo¹,

Dondio²,

Delany³

et al. 2016

IFIP Advances in Information and Communication Technology

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“…Argumentation Theory (AT) provides computational models for the implementation of defeasible reasoning [14], or reasoning when a conclusion can be changed in the light of new evidence. It has become progressively central in the AI domain for implementing non-monotonic reasoning [2,5].…”

Section: Related Workmentioning

confidence: 99%

A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers

Rizzo¹,

Majnarić

Longo³

2018

Lecture Notes in Computer Science

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Computational argumentation has been gaining momentum as a solid theoretical research discipline for inference under uncertainty with incomplete and contradicting knowledge. However, its practical counterpart is underdeveloped, with a lack of studies focused on the investigation of its impact in real-world settings and with real knowledge. In this study, computational argumentation is compared against non-monotonic fuzzy reasoning and evaluated in the domain of biological markers for the prediction of mortality in an elderly population. Different non-monotonic argument-based models and fuzzy reasoning models have been designed using an extensive knowledge base gathered from an expert in the field. An analysis of the true positive and false positive rate of the inferences of such models has been performed. Findings indicate a superior inferential capacity of the designed argument-based models.

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“…A reasoning process is defeasible when accounted arguments are rationally compelling but not deductively valid. Argumentation systems are typically constructed upon an underlying logical language and are generally built on four layers (Longo and Dondio 2014): DR is also known as NMR because of the technical property (non-monotonicity) of the logical formalisms that are aimed at modelling DR activity (Baroni, Guida, and Mussi 1997).…”

Section: Mwl As a Defeasible Phenomenonmentioning

confidence: 99%

“…A wide range of ad hoc definitions of MWL can be found in the literature. AT can lead to explanatory reasoning and is a paradigm that allows the representation of a construct to be retracted and updated with additional knowledge (Longo and Dondio 2014). However, 'it is not an elementary property, rather it emerges from the interaction between the requirements of a task, the circumstances under which it is performed and the skills, behaviours and perceptions of the operator' (Hart and Staveland 1988).…”

Section: Introductionmentioning

confidence: 99%

A defeasible reasoning framework for human mental workload representation and assessment

Longo

2015

Behaviour & Information Technology

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Human mental workload (MWL) has gained importance in the last few decades as an important design concept. It is a multifaceted complex construct mainly applied in cognitive sciences and has been defined in many different ways. Although measuring MWL has potential advantages in interaction and interface design, its formalisation as an operational and computational construct has not sufficiently been addressed. This research contributes to the body of knowledge by providing an extensible framework built upon defeasible reasoning, and implemented with argumentation theory (AT), in which MWL can be better defined, measured, analysed, explained and applied in different human-computer interactive contexts. User studies have demonstrated how a particular instance of this framework outperformed state-of-the-art subjective MWL assessment techniques in terms of sensitivity, diagnosticity and validity. This in turn encourages further application of defeasible AT for enhancing the representation of MWL and improving the quality of its assessment.

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Defeasible Reasoning and Argument-Based Systems in Medical Fields: An Informal Overview

Cited by 13 publications

References 30 publications

Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile

Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile

A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers

A defeasible reasoning framework for human mental workload representation and assessment

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