7 research outputs found
Interference Effects in Quantum Belief Networks
Probabilistic graphical models such as Bayesian Networks are one of the most
powerful structures known by the Computer Science community for deriving
probabilistic inferences. However, modern cognitive psychology has revealed
that human decisions could not follow the rules of classical probability
theory, because humans cannot process large amounts of data in order to make
judgements. Consequently, the inferences performed are based on limited data
coupled with several heuristics, leading to violations of the law of total
probability. This means that probabilistic graphical models based on classical
probability theory are too limited to fully simulate and explain various
aspects of human decision making.
Quantum probability theory was developed in order to accommodate the
paradoxical findings that the classical theory could not explain. Recent
findings in cognitive psychology revealed that quantum probability can fully
describe human decisions in an elegant framework. Their findings suggest that,
before taking a decision, human thoughts are seen as superposed waves that can
interfere with each other, influencing the final decision.
In this work, we propose a new Bayesian Network based on the psychological
findings of cognitive scientists. We made experiments with two very well known
Bayesian Networks from the literature. The results obtained revealed that the
quantum like Bayesian Network can affect drastically the probabilistic
inferences, specially when the levels of uncertainty of the network are very
high (no pieces of evidence observed). When the levels of uncertainty are very
low, then the proposed quantum like network collapses to its classical
counterpart
Unifying Decision-Making: a Review on Evolutionary Theories on Rationality and Cognitive Biases
In this paper, we make a review on the concepts of rationality across several
different fields, namely in economics, psychology and evolutionary biology and
behavioural ecology. We review how processes like natural selection can help us
understand the evolution of cognition and how cognitive biases might be a
consequence of this natural selection. In the end we argue that humans are not
irrational, but rather rationally bounded and we complement the discussion on
how quantum cognitive models can contribute for the modelling and prediction of
human paradoxical decisions
Introducing Quantum-Like Influence Diagrams for Violations of the Sure Thing Principle
It is the focus of this work to extend and study the previously proposed
quantum-like Bayesian networks to deal with decision-making scenarios by
incorporating the notion of maximum expected utility in influence diagrams. The
general idea is to take advantage of the quantum interference terms produced in
the quantum-like Bayesian Network to influence the probabilities used to
compute the expected utility of some action. This way, we are not proposing a
new type of expected utility hypothesis. On the contrary, we are keeping it
under its classical definition. We are only incorporating it as an extension of
a probabilistic graphical model in a compact graphical representation called an
influence diagram in which the utility function depends on the probabilistic
influences of the quantum-like Bayesian network.
Our findings suggest that the proposed quantum-like influence digram can
indeed take advantage of the quantum interference effects of quantum-like
Bayesian Networks to maximise the utility of a cooperative behaviour in
detriment of a fully rational defect behaviour under the prisoner's dilemma
game
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A quantum probability account of individual differences in causal reasoning
We use quantum probability (QP) theory to investigate individual differences in causal reasoning. By analyzing data sets from Rehder (2014) on comparative judgments, and from Rehder & Waldmann (2016) on absolute judgments, we show that a QP model can both account for individual differences in causal judgments, and why these judgments sometimes violate the properties of causal Bayes nets. We implement this and previously proposed models of causal reasoning (including classical probability models) within the same hierarchical Bayesian inferential framework to provide a detailed comparison between these models, including computing Bayes factors. Analysis of the inferred parameters of the QP model illustrates how these can be interpreted in terms of putative cognitive mechanisms of causal reasoning. Additionally, we implement a latent classification mechanism that identifies subcategories of reasoners based on properties of the inferred cognitive process, rather than post hoc clustering. The QP model also provides a parsimonious explanation for aggregate behavior, which alternatively can only be explained by a mixture of multiple existing models. Investigating individual differences through the lens of a QP model reveals simple but strong alternatives to existing explanations for the dichotomies often observed in how people make causal inferences. These alternative explanations arise from the cognitive interpretation of the parameters and structure of the quantum probability model
Climate Change Denial and Public Relations
This is the first book on climate change denial and lobbying that combines the ideology of denial and the role of anthropocentrism in the study of interest groups and communication strategy. Climate Change Denial and Public Relations: Strategic Communication and Interest Groups in Climate Inaction is a critical approach to climate change denial from a strategic communication perspective. The book aims to provide an in-depth analysis of how strategic communication by interest groups is contributing to climate change inaction. It does this from a multidisciplinary perspective that expands the usual approach of climate change denialism and introduces a critical reflection on the roots of the problem, including the ethics of the denialist ideology and the rhetoric and role of climate change advocacy. Topics addressed include the power of persuasive narratives and discourses constructed to support climate inaction by lobbies and think tanks, the dominant human supremacist view and the patriarchal roots of denialists and advocates of climate change alike, the knowledge coalitions of the climate think tank networks, the denial strategies related to climate change of the nuclear, oil, and agrifood lobbies, the role of public relations firms, the anthropocentric roots of public relations, taboo topics such as human overpopulation and meat-eating, and the technological myth. This unique volume is recommended reading for students and scholars of communication and public relations