Title
Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process.
Abstract
Recently a novel quantum information formalism - quantum adaptive dynamics - was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schroer stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a "big Kolmogorov space" as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.
Year
DOI
Venue
2016
10.1142/S1230161216500116
OPEN SYSTEMS & INFORMATION DYNAMICS
Field
DocType
Volume
Quantum,Quantum probability,Quantum cognition,Information processing,Quantum mechanics,Unconscious inference,Artificial intelligence,Quantum information science,Statistics,Quantum information,Visual perception,Mathematics
Journal
23
Issue
ISSN
Citations 
2
1230-1612
0
PageRank 
References 
Authors
0.34
3
5
Name
Order
Citations
PageRank
Luigi Accardi1116.36
Andrei Khrennikov214335.01
Masanori Ohya37419.14
Yoshiharu Tanaka4144.06
Ichiro Yamato511.71