Modelling contextuality amidst causal influences by means of a computationally tractable combinatorial approach

Obeid, Abdul Karim

doi:10.5204/thesis.eprints.226105

Cited by 2 publications

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“…Within the study of contextuality, there are numerous modeling approaches that stem from distinct interpretations and formalisms of the phenomenon (Isham and Butterfield, 1998 ; Spekkens, 2005 ; Asano et al, 2014b ; Cabello et al, 2014 ; Acín et al, 2015 ; Dzhafarov and Kujala, 2016 ; Khrennikov, 2021 ). This work continues upon previous research undertaken by Obeid ( 2021 ) in the manner of the combinatorial approach of Acín et al ( 2015 ), for determining quantum-like contextuality amidst causal influences. To the best of our knowledge, the only other line of research that has addressed the forementioned issues for determining of quantum-like contextuality is that of Jones ( 2019 ).…”

Section: Related Worksupporting

confidence: 70%

An Extension of Combinatorial Contextuality for Cognitive Protocols

et al. 2022

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This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cognition, in systems relating to mental phenomena, such as concepts in human memory. In the cognitive field of study, a contemporary challenge facing the determination of whether a phenomenon is contextual has been the identification and management of disturbances. Whether or not said disturbances are identified through the modeling approach, constitute causal influences, or are disregardableas as noise is important, as contextuality cannot be adequately determined in the presence of causal influences. To address this challenge, we first provide a formalization of necessary elements of the combinatorial approach within the language of canonical causal models. Through this formalization, we extend the combinatorial approach to support a measurement and treatment of disturbance, and offer techniques to separately distinguish noise and causal influences. Thereafter, we develop a protocol through which these elements may be represented within a cognitive experiment. As human cognition seems rife with causal influences, cognitive modelers may apply the extended combinatorial approach to practically determine the contextuality of cognitive phenomena.

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Section: Related Worksupporting

confidence: 70%

An Extension of Combinatorial Contextuality for Cognitive Protocols

et al. 2022

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“…This work continues upon previous research undertaken by Obeid [2021] in the manner of the combinatorial approach, for determining quantum-like contextuality amidst causal influences. To the best of our knowledge, the only other line of research that has addressed the forementioned issues for determining of quantum-like contextuality is that of Jones [2019].…”

Section: Related Worksupporting

confidence: 57%

An Extension Of Combinatorial Contextuality For Cognitive Protocols

Obeid¹,

Bruza²,

Moreira³

et al. 2022

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This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cognition, in systems relating to mental phenomena, such as concepts in human memory [Aerts et al., 2013]. In the cognitive field of study, a contemporary challenge facing the determination of whether a phenomenon is contextual has been the identification and management of disturbances . Whether or not said disturbances are identified through the modelling approach, constitute causal influences, or are disregardableas as noise is important, as contextuality cannot be adequately determined in the presence of causal influences [Gleason, 1957]. To address this challenge, we first provide a formalisation of necessary elements of the combinatorial approach within the language of canonical causal models. Through this formalisation, we extend the combinatorial approach to support a measurement and treatment of disturbance, and offer techniques to separately distinguish noise and causal influences. Thereafter, we develop a protocol through which these elements may be represented within a cognitive experiment. As human cognition seems rife with causal influences, cognitive modellers may apply the extended combinatorial approach to practically determine the contextuality of cognitive phenomena.

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Modelling contextuality amidst causal influences by means of a computationally tractable combinatorial approach

Cited by 2 publications

References 0 publications

An Extension of Combinatorial Contextuality for Cognitive Protocols

An Extension of Combinatorial Contextuality for Cognitive Protocols

An Extension Of Combinatorial Contextuality For Cognitive Protocols

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