Shared awareness is an essential concept in the joint decision-making context. Typically, it is oversimplified and associated with shared information. To share an understanding in totality is to say that there is a sharing of meaning and awareness, not only of information. However, existing shared awareness models fail to explain situations in which two people view the same event but attend to different information or act differently based on the same information. Although several categorization models of shared awareness exist, the models are ad-hoc or inadequate to generalization. This paper presents a theoretical discussion of shared awareness based on its cognitive structure. We apply the pragmatic idealism framework, which provides a theoretical construct where the domain of awareness is an abstraction of reality. This framework supports the existence of multiple incompatible perspectives and understandings. We discuss the ontology of this abstract concept with the mathematical tools of quantum probability theory. We discuss the cognitive processes that transform a simple situation into a complex situation. The presented model of shared awareness includes a quantification of the degree of sharing in complex situations.
Shared awareness is an essential concept in the joint decision-making context. Typically, it is oversimplified and associated with shared information. To share an understanding in totality is to say that there is a sharing of meaning and awareness, not only of information. However, existing shared awareness models fail to explain situations in which two people view the same event but attend to different information or act differently based on the same information. Although several categorization models of shared awareness exist, the models are ad-hoc or inadequate to generalization. This paper presents a theoretical discussion of shared awareness based on its cognitive structure. We apply the pragmatic idealism framework, which provides a theoretical construct where the domain of awareness is an abstraction of reality. This framework supports the existence of multiple incompatible perspectives and understandings. We discuss the ontology of this abstract concept with the mathematical tools of quantum probability theory. We discuss the cognitive processes that transform a simple situation into a complex situation. The presented model of shared awareness includes a quantification of the degree of sharing in complex situations.
Two people in the same situation may ascribe very different meanings to their experiences. They will form different awareness, reacting differently to shared information. Various factors can give rise to this behavior. These factors include, but are not limited to, prior knowledge, training, biases, cultural factors, social factors, team vs. individual context, time, resources, and technology. At the individual level, the differences in attaining separate actions by accessing shared information may not be considered as an anomaly from the perspective of rational decision-making. But for group behavior, reacting differently to the shared information can give rise to conflicts and deviations from an expected behavior, and are categorized as an anomaly or irrational behavior. The lack of proper recognition of the reasons for differences can even impede the shared action towards attaining a common objective. The manifestation of differences becomes noticeable in complex situations. The shared awareness approaches that originate from available situational awareness models fail to recognize the reasons of an unexpected decision in these situations. One reason for this is that in complex situations, incompatible events can become dominant. Human information processing is sensitive to the compatibility of the events. This, and various other human psychological characteristics, require models to be developed that include comprehensive formalisms for both compatible and incompatible events in complex situations. Quantum probability provides a geometrical probabilistic formalism to study the decision and the dynamic cognitive systems in complex situations. The event representation in Hilbert space provides the necessary foundation to represent an individual's knowledge of a situation. Hilbert space allows representing awareness as a superposition of indefinite states. These states form a complete N-dimensional Hilbert space. Within the space generated, events are represented as a subspace. By using these characteristics of Hilbert space and quantum geometrical probabilities, this study introduces a representation of self and other-than-self in a situation. An area of awareness with the possibility of projection onto the same event allows representing shared awareness geometrically. This formalism provides a coherent explanation of shared awareness for both compatible and incompatible events. Also, by using the superposition principles, the dissertation introduces spooky action at a distance concept in studying shared awareness.
Growing empirical evidence reveals that traditional set-theoretic structures cannot in general be applied to cognitive phenomena. This has raised several problems, as illustrated, for example, by probability judgement errors and decision-making (DM) errors. We propose here a unified theoretical perspective which applies the mathematical formalism of quantum theory in Hilbert space to cognitive domains. In this perspective, judgements and decisions are described as intrinsically non-deterministic processes which involve a contextual interaction between a conceptual entity and the cognitive context surrounding it. When a given phenomenon is considered, the quantum-theoretic framework identifies entities, states, contexts, properties and outcome statistics, and applies the mathematical formalism of quantum theory to model the considered phenomenon. We explain how the quantum-theoretic framework works in a variety of judgement and decision situations where systematic and significant deviations from classicality occur.
This is a unique text that explores quantum-like modelling frameworks that connect quantum mechanics with cognitive science and consciousness studies to propose a new ontological framework that transcends traditional boundaries between physics, philosophy, and cognitive science. The book develops along two complementary paths. First, it explores quantum-like modelling, an exciting emerging field where researchers apply logical and mathematical structures from quantum mechanics and information theory to cognitive modelling and decision science. Second, it investigates the profound links between quantum science and consciousness studies, incorporating insights from advanced mathematical frameworks such as category theory. By synthesizing these two approaches, the authors propose a novel framework termed 'quantum-like reality' that moves beyond pragmatic modelling to offer deeper ontological thinking that can enrich both foundational understanding and applied research. This will be an interesting read for students and researchers working at the intersection of quantum physics, cognitive science, and consciousness studies.
A Virtual Reality (VR) system is introduced in a modified Observe, Orient, Decide and Act (OODA) model for supporting information sharing and situational awareness in a complex environment. At the same time the cooperation and interaction with technical systems provided organizational process support, guidance, and monitoring of system critical functions.The OODA-VR combination enabled bringing together theoretical discussion and practicality responses in dyadic interactions. With the integration of simulation and reality metaphors the reasoning process takes advantage of environmental and cognitive knowledge constructed from complexity tasks. From an interaction viewpoint a more holistic view has been performed in relation to the problem space to articulate the thinking and decision-making process.The provision of the VR interaction capability has been extended to reshape quantum formalism and reality and complement the measurement collapse theory. This baseline has been explored through the Theory of Decoherence and Everettian quantum mechanics representing different measurements outcomes on a system.
Experiments in cognitive science and decision theory show that the ways in which people combine concepts and make decisions cannot be described by classical logic and probability theory. This has serious implications for applied disciplines such as information retrieval, artificial intelligence and robotics. Inspired by a mathematical formalism that generalizes quantum mechanics the authors have constructed a contextual framework for both concept representation and decision making, together with quantum models that are in strong alignment with experimental data. The results can be interpreted by assuming the existence in human thought of a double-layered structure, a 'classical logical thought' and a 'quantum conceptual thought', the latter being responsible of the above paradoxes and nonclassical effects. The presence of a quantum structure in cognition is relevant, for it shows that quantum mechanics provides not only a useful modeling tool for experimental data but also supplies a structural model for human and artificial thought processes. This approach has strong connections with theories formalizing meaning, such as semantic analysis, and has also a deep impact on computer science, information retrieval and artificial intelligence. More specifically, the links with information retrieval are discussed in this paper.
Quantum probability theory (QPT) has provided a novel, rich mathematical framework for cognitive modelling, especially for situations which appear paradoxical from classical perspectives. This work concerns the dynamical aspects of QPT, as relevant to cognitive modelling. We aspire to shed light on how the mind's driving potentials (encoded in Hamiltonian and Lindbladian operators) impact the evolution of a mental state. Some existing QPT cognitive models do employ dynamical aspects when considering how a mental state changes with time, but it is often the case that several simplifying assumptions are introduced. What kind of modelling flexibility does QPT dynamics offer without any simplifying assumptions and is it likely that such flexibility will be relevant in cognitive modelling? We consider a series of nested QPT dynamical models, constructed with a view to accommodate results from a simple, hypothetical experimental paradigm on decision-making. We consider Hamiltonians more complex than the ones which have traditionally been employed with a view to explore the putative explanatory value of this additional complexity. We then proceed to compare simple models with extensions regarding both the initial state (e.g. a mixed state with a specific orthogonal decomposition; a general mixed state) and the dynamics (by introducing Hamiltonians which destroy the separability of the initial structure and by considering an open-system extension). We illustrate the relations between these models mathematically and numerically.This article is part of the themed issue 'Second quantum revolution: foundational questions'.